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\title{“I am uncertain” vs “It is uncertain”. How linguistic markers of the uncertainty source affect uncertainty communication.}

\author{Marie Juanchich \thanks{Department of Psychology, University of Essex,
  Wivenhoe Park, CO4 3SQ, Colchester, UK. E-mail:
  m.juanchich@essex.ac.uk.} \and Amélie
Gourdon-Kanhukamwe\thanks{Department of Management,Kingston Business
  School, Kingston University.} \and Miroslav Sirota
\thanks{Department of Psychology, University of Essex.}
}

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Two psychological sources of uncertainty bear implications for
judgment and decision-making: external uncertainty is seen as stemming from
properties of the world, whereas internal uncertainty is seen as stemming from lack
of knowledge. The apparent source of uncertainty can be conveyed through
linguistic markers, such as the pronoun of probability phrases (e.g., I
am uncertain vs.\ It is uncertain). Here, we investigated whether and
when speakers use different pronoun subjects as such linguistic markers
(Exp.\ 1 and 2) and what hearers infer from them (Exp.\ 3 and 4).
Speakers more often described higher probabilities and knowable
outcomes with internal probability phrases. In dialogue, speakers
mirrored the source of their conversational partner. Markers of the
source had a main effect or interacted with the probability conveyed
and speaker expertise to shape the judgments and decisions of hearers.
For example, experts voicing an internal probability phrase were judged
as more knowledgeable than experts using an external probability phrase
whereas the result was the opposite for lay speakers. We discuss how
these findings inform our understanding of subjective uncertainty and uncertainty
communication theories.

\smallskip
\noindent
Keywords: uncertainty communication, source of uncertainty, subject pronoun,
pragmatics
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{\renewcommand{\thefootnote}{}

\footnotetext{

The authors thank Karl Halvor Teigen for inputs on the design of the
experiment, data collection for Experiment 2 and comments on the
manuscript, and Jean-François Bonnefon for insightful discussions. Special thanks also to Jonathan Baron for his contribution to the paper.

Copyright: \copyright\ 2017.
The authors license this article under the terms of the
\href{http://creativecommons.org/licenses/by/3.0/}{Creative Commons
  Attribution 3.0 License.}
}}

\saythanks

\section{Introduction}

Uncertainty can seem to stem from a lack of knowledge – and be internal – or
from the properties of the environment – and be external (e.g.,
Kahneman \& Tversky, 1982). The apparent source of uncertainty acts as an
important determinant of probability judgment and subsequent
decision-making (e.g., Brun \& Teigen, 1990; Fox \& Ülkümen, 2011;
Kahneman \& Tversky, 1982; Knight, 1921; Ülkümen, Fox \& Malle, 2016).
Therefore, the use and interpretation of linguistic markers of the
source is important to understand. It has been suggested that speakers
choose probability phrases bearing specific pragmatic markers to
convey the source of their uncertainty (Fox \& Ülkümen, 2011; Kahneman
\& Tversky, 1982; Teigen, 1988b). In this paper, we aimed to provide
direct evidence for such a claim. We focused on a subtle property of
probability phrases marking the source of uncertainty of the speaker –
the subject pronoun of probability phrases (e.g., \textit{I}
\textit{am} \textit{uncertain} vs.\ \textit{It} \textit{is}
\textit{uncertain}). Specifically, we assessed here the determinants
of the pronoun subject of probability phrases\footnote{ In the present
  paper, we have chosen the label \textit{probability} because this
  concept can be easily compared and mapped on the numerical
  probability scale. The term \textit{uncertainty }might be considered
  more adequate than the term \textit{probability} due to its more
  generic nature, but we have discarded it because the scalar
  properties of an uncertainty scale are less obvious. For example,
  being “more uncertain”, could mean being closer to 0\% or closer to
  an ignorance prior such as 50\% for a dichotomous outcome), whereas
  an event that is “more probable” is clearly closer to 1. We have
  chosen the label \textit{phrase} because we focus on a phrase, not
  on a term or a single word.} for speakers (Experiments 1 and 2) and
their consequences for recipients’ judgments and decision-making
(Experiments 3 and 4).

\subsection{The source of uncertainty}

The traditional theoretical frameworks of perceived uncertainty describe two forms
of uncertainty: internal and external uncertainty (Fox \& Ülkümen,
2011; Hacking, 1975; Kahneman \& Tversky, 1982; Lagnado \& Sloman,
2007). Internal uncertainty stems from a lack of personal knowledge.
For instance, when one thinks that the Eiffel Tower is
\textit{probably} more than 300m high, the uncertainty is internal, and
attributable to the level of one’s own (lack of) knowledge. External
uncertainty stems from uncertainty attributable to processes in the
external world (Kahneman \& Tversky, 1982), and can be based on
frequencies, and hence generate a distributional uncertainty, or based
on propensity and hence generate a dispositional uncertainty (also
called singular uncertainty). For example, one can bet on a horse based
on the number of times she won a race in the past (i.e., distributional
external uncertainty), or based on her current health record (i.e.,
dispositional external uncertainty). Kahneman and Tversky acknowledged
that, in most cases, uncertainty is a mixture of internal and external
sources. 

Most empirical work use the terms epistemic and internal
interchangeably (Løhre \& Teigen, 2016; Robinson, Pendle, Rowley \&
Beck, 2009; Teigen \& Løhre 2017; Volz, Schubotz \& Von Cramon, 2004,
2005), apparently making no distinction. However, a more recent
account draws a distinction between these categories (Fox \& Ülkümen,
2017; Ülkümen et al., 2016).  Ülkümen et al.\ (2016)
outlined two variants of subjective uncertainty: epistemic and
aleatory. In their model, epistemic uncertainty is characterized by
inadequate knowledge or skills and aleatory uncertainty by stochastic
behaviors. Epistemic uncertainty usually applies to single cases with
binary truth value whereas aleatory uncertainty concerns classes of
possible events. Ülkümen et al.\ (2016) introduced the concepts of 
internal and external uncertainty as distinct from epistemic and aleatory
uncertainty. The internal-external dimension refers to the
physical source of uncertainty: is the uncertainty happening in a
person's mind (and is internal) or is it “out there” (e.g.,
uncertainty about the outcome of a future race).

The accounts of uncertainty proposed by Kahneman and Tversky (1982)
and Ülkümen et al.\ (2016) use a similar terminology
(internal-external; epistemic-aleatory), but this terminology covers
slightly different concepts. For Kahneman and Tversky, internal was
synonymous to epistemic whereas Ülkümen and Fox's account treat the
internal-external dimension and the aleatory-epistemic dimensions as
different and logically independent.  For example, they posit that
epistemic uncertainty can both be internal and external and that in
both cases it would be best conveyed with confidence quantifiers
(e.g., \textit{confident}, \textit{certain}, \textit{sure}), whereas
internal or external distributional uncertainty would be a form of
aleatory uncertainty and would be best conveyed with likelihood
quantifiers (e.g., likelihood, probability, chance). The present paper
takes no position on whether epistemic and internal are
identical. Although the model of Ülkümen and Fox makes sense, we do not address
it, because our concern is with the internal/external distinction only.

From a normative point of view, two probabilities, equal in magnitude,
should be treated in the same way, regardless of their
source. Psychologically, however, this is not the case: the sources of
uncertainty has an effect on judgment, decision-making and reasoning.
Fox and Ülkümen (2011) suggested that it is because internal and
external uncertainties rely on ``distinct information, weights and/or
processes'' (p.\ 25). Fox and Ülkümen marshalled evidence of such
effects from different fields. For example, in hypothetical scenarios,
people prefer to bet on a die that will be cast (external uncertainty)
rather than on a die that has already been cast without them seeing
the outcome (internal uncertainty; Heath \& Tversky, 1991; Rothbart \&
Snyder, 1970). In real life situations, peoples’ bet preference is
reversed, because they prefer to guess after the die has been thrown
(Robinson et al., 2009).

\subsection{Linguistic markers of the uncertainty source}

Prior research hypothesized that the source of uncertainty can be
conveyed through the use of specific words: linguistic markers of the
source (Fox \& Ülkümen, 2011; Kahneman \& Tversky, 1982; Teigen,
1988a). However, only scarce empirical evidence has been accumulated to
support this hypothesis (Løhre \& Teigen, 2016; Ülkümen et al., 2016).
The grammatical subject of probability phrases was the main candidate
of such a marker (Kahneman \& Tversky, 1982; Løhre \& Teigen, 2016).
The subject of probability phrases indicate “who” or “what” is
uncertain and it is hence logical that first person pronouns would be
more characteristic of internal uncertainties, whereas third person
neutral pronouns (i.e., it) would be more appropriate to convey
external sources of uncertainty.

\subsection{When do speakers choose “I” and “it”?}

Fox, Ulkumen and Malle (2011) tested the way people choose markers of
the source of uncertainty when communicating
uncertainty.\footnote{Their findings are also cited as Fox and Malle
  (1997) in Fox and Irwin, (1988).} Fox and colleagues employed a
paradigm in which the source of uncertainty was manipulated through
the pronoun subject of the probability phrase or the pronoun and a
verbal probability associated in both cases with a numerical
probability (see respectively Examples 1 and 2):

\medskip
\noindent % try this
{\itshape Example 1.}

A: \textit{I am} 70\% sure that Bush will be elected US president again

B: \textit{There is} a 70\% chance that Bush will be elected US
president again

\medskip
\noindent
{\itshape Example 2.}

A: Bennie is 60\% \textit{sure} that Team A will beat Team B next week.

B: Bob believes there is a 60\% \textit{chance} that Team B will beat
team A next week.
\medskip

Fox and Malle (1997) identified a general preference for external
probability phrases that can change with contextual factors. Most
participants deemed external probability phrases to be more appropriate
than internal ones to predict a range of 16 world outcomes. For
example, 78\% of the participants predicted the outcome of the 1992
American presidential election with an external probability phrase
(Example 1, Sentence B). The subject pronoun was shown to relate to the
probability conveyed by the speaker. Speakers selected more often an
internal probability phrase to convey a higher probability (e.g.,
``I am X\% confident that Minnesota will beat Cincinnati''),
whereas they preferred an external probability phrase to convey a low
probability (e.g., ``I think there is an X\% probability that
Minnesota will beat Cincinnati''; Study 4). Furthermore, knowledge and
expertise of a speaker moderates the use of external phrases. For
example, speakers (especially those with higher internal locus of
control) selected a confidence term to describe self-related events
more often than to describe world events (e.g., ``I will go to
bed before midnight'') (Fox \& Malle, 1997; Ülkümen et al., 2016).
Interestingly, more knowledgeable speakers were more willing to
communicate their uncertainty with confidence terms than less
knowledgeable speakers (e.g., Americans predicting the outcome of the
American election vs.\ the German election). 

\subsection{Effect of the source of uncertainty on hearers}

Limited evidence suggests that hearers take linguistic markers of
uncertainty into consideration when interpreting uncertainty. When
making inferences, the hearers expected a higher probability threshold
to be convinced by “I” probability phrases than by “it” probability
phrases (Løhre \& Teigen, 2016). Participants judged that a 60\%
external probability was the minimal probability required to advise a
patient to take a new treatment, whereas the threshold was about 69\%
for an internal probability phrase (Løhre \& Teigen, 2016). The same
pattern was found in different contexts, such as regarding advice in
exam revision. However, the effect of the subject on perceived
knowledge of the speaker was not consistent across the five
experiments. Recipients inferred that speakers uttering internal
probability phrases were more knowledgeable than speakers uttering
external probability phrases, in one study whereas in two other, the
mean differences were not statistically significant (Løhre \& Teigen,
2016; Experiment 1 vs.\ Experiment 3 and 4). When making decisions,
the communicated source of uncertainty had a more consistent
effect. In Fox and Malle’s studies (1997), participants made simple
binary choices and read an internal and an external probability phrase
describing each option, as in Example 3 below. Most participants
(60--70\%) preferred the house where the expert described the
earthquake risk with an internal probability phrase. The finding was
replicated with different vignettes in two other studies.

\medskip
\noindent
{\itshape Example 3.}
\begin{itemize}
\item A: ``I believe there is a 95\% chance that Home A
will withstand an earthquake of magnitude 7 or less.''
\item B: ``I am 95\% sure that Home B will withstand an
earthquake of magnitude 7 or less.''
\end{itemize}
\medskip

Further, recipients’ preference for internal probability phrases
interacted with the expertise of the speakers: most of the participants
preferred to follow an internal probability advice voiced by a
professor, whereas most preferred to follow the external probability
advice voiced by an undergraduate (Fox \& Malle, 1997; Listener – Study
2). This finding was taken as indirectly indicating that the source of
uncertainty provided recipients with information about the data that
were used or the processes by which uncertainty was assessed:
participants were keen to rely on the personal belief of an expert, but
would rather rely on a more factually based opinion from a novice (Fox
\& Malle, 1997).

\subsection{Is the subject marking the source of uncertainty? The controversy}

Some authors however dispute the possibility that the subject of
uncertainty sentences marks the source of uncertainty. Fox and Ülkümen
(2017); and Ülkümen et al.\ (2016) proposed that the subject of
probability phrases does not convey the source but the subjectivity of
the uncertainty. They tested this hypothesis by showing that a range of
numerical probability phrases (e.g., ``I am 80\% sure'' vs.\ ``It is 80\%
sure'') with varying subjects led to variation in subjectivity
perception. Participants assessed eight sentences that had four
probability quantifiers (e.g., \textit{confidence}, \textit{sure},
\textit{probability}, and \textit{chance}) and that either featured the
grammatical subject “I” or “it”. This combination however was not
always grammatically possible (e.g., \textit{I am 80\% probability}),
so the phrases for which the sentence did not make sense were
complemented with an extra verb and subject (e.g., ``I think
there is an 80\% probability'').

\begin{table*}[t]
\caption{The four accounts describing the function of the subject of probability
phrases along with their experimental manipulation.}
\begin{tabular}{L{1.3in}L{1.3in}L{1.3in}L{1.3in}L{1.3in}}\toprule
Accounts & Kahneman and Tversky (1982) & Fox and Ülkümen (2017)  & Løhre and Teigen (2016); Teigen and Løhre (2017) & Juanchich et al., 2017 (present paper)\\\midrule
Dimension marked & Internal-external  & Subjective-Objective (“voice”)  & Internal-external
 & Internal-external \\
Terminology and definition & Not different from epistemic-aleatory and related to subjectivity & Logically independent from the epistemic-aleatory dimension and from the
internal-external dimension & Synonymous to epistemic-aleatory and related to subjectivity.  & Synonymous to epistemic-aleatory and related to subjectivity\\
Manipulation & {}-{}- & Voice (subject or subject + modal) & Subject (+ numerical probability)$^*$ & Subject\\
Example of manipulation & {}-{}- & Subj: I‘d say there is an 80\% probability  & Int: I am 57\% certain… &
   Int: I am uncertain…\\
      & & Obj: There is an 80\% probability & Ext: It is 45\% certain… & Ext: It is uncertain…\\\bottomrule
\mc{5}{p{6.5in}}{$^*$ The example provided shows the average numerical probability provided
by participants. Note also that in one of the studies only the subject
was manipulated, to assess its effect on probability judgments: “How
certain are you – vs.\ how certain is it – Expe 5a.}
\end{tabular}
\end{table*}

Participants judged whether the sentence elicited a more singular or
distributional reasoning (“the current signs point to rain tomorrow”
was expected to measure singular reasoning and “most of the time there
are signs like this it rains the next day” was expected to measure
distributional reasoning). The subjectivity was assessed on a scale
ranging from 1: ``The sentence reflects the speaker’s own
subjective opinion'' to 4: ``The sentence reflects objective
facts, computation and/or consensus''. Results showed that the “I”
probability phrases were perceived as more subjective than the “it”
ones. Further, the subject interacted with the quantifier type
(\textit{chance} and \textit{probability} vs.\ \textit{confidence} and
\textit{sure}) showing that subjectivity also depended on the type of
quantifier used. It is also important to note that the subject did not
have an effect on the perceived reasoning of the speaker, showing that
it did not discriminate between case based reasoning and distributional
one.

Teigen and Løhre (2017) disagreed with the proposition that the subject
describes the subjectivity of uncertainty and not its source. They
agree that the subject is a clue for subjectivity, but they argue that
this is because it indicates who or what is being uncertain. The argument
for the claim that the subject of probability phrases marks the source
of uncertainty is that the same probability term, such as “uncertain”,
can be used with different subject pronouns, some of which refer to an
object or to nothing (e.g. \textit{it} is uncertain) and some of which
refer to a person (e.g., \textit{I} am uncertain). Teigen and Løhre
(2017)’s approach is closer to the original proposal by Kahneman and
Tversky (1982), where epistemicness and internal uncertainty are not
differentiated, and which assumes that internal uncertainty is also
more subjective than external uncertainty. The focus of the five papers
linking the subject of uncertainty phrases to the variants of
uncertainty is summarized in Table 1 to provide an easier grasp of the
current landscape. 

Thus, the review of the existing frameworks shows a lack of consensus
regarding the role of the subject of probability phrases. Existing
findings also fall short of providing unambiguous evidence of the role
of the subject, because the pronoun manipulation was often confounded
with some other features of probability phrases. In Teigen and Løhre
(2017), the pronoun was manipulated but participants could associate
different numerical probability with it (Experiments 2 and 4), hence
confounding the internality with the probability dimension. When the
probability did not vary, it was the type and syntactic category of
the probability term that varied (e.g., certainty vs.\ probability,
Experiment 3). As suggested by Teigen and Løhre (2017), in Fox and
Ülkümen (2017), some phrases presented as featuring a first person
pronoun actually featured two grammatical subjects and two uncertainty
quantifiers (e.g., “I think there is an 80\% probability”), for which
the scores were aggregated with simpler sentences “e.g., “I am 80\%
certain”) and compared to a set of simple “it” sentences such as “it
is 80\% certain” and “there is an 80\% probability”. This syntactical
imbalance is likely to have led to variations in the probability
conveyed by the phrases. This variation is in line with research in
linguistics where modals are considered as quantifiers of uncertainty
(Biber, Finegan, Johansson, Conrad \& Leech, 1999). In the only
experiment where the pronoun was not confounded with other variables
(Teigen \& Løhre 2017, Experiment 1), the data indicated that external
phrases were judged as being more informative and uttered by more
knowledgeable speakers.

\subsection{Present research}

Prior research indicates that linguistic markers of the source of
uncertainty play a role in communicating and interpreting uncertainty
phrases. However, we cannot draw firm conclusions regarding the role
of the subject as a marker of the source of uncertainty for two
reasons.  First, the evidence of the role of the subject is mixed
(Løhre \& Teigen, 2016) and the view that the subject is a marker of
the source was recently challenged (Fox \& Ülkümen, 2017). Second, the
manipulation of the subject used in the prior research might have been
consistently confounded with other factors: the probability conveyed
(Fox \& Ülkümen, 2017; Løhre \& Teigen, 2016), the probability term
and its phrasal category (Løhre \& Teigen, 2016), and the number of
probability terms in the phrase (Fox \& Ülkümen, 2017; Ülkümen et al.,
2016). Although the confounding effects were sometimes controlled
statistically, robust experimental evidence is missing. We propose to
provide it here using parsimonious manipulation of the subject while
keeping the other dimensions constant. Thus, the current research
builds on the previous research but strengthens its contribution by
providing additional evidence, while removing possible confounding
variables.

In the present manuscript, Experiments 1 and 2 were designed to test
whether characteristics associated with the source of uncertainty
(e.g., the time of occurrence of an event) predicted the use of a
specific pronoun subject (i.e., ``I'' vs.\ ``it''). We then tested in
Experiments 3 and 4 the effect of the subject of probability phrases
on recipients’ inferences. Hence we propose to test how speakers use
“I” and “it” when communicating their uncertainty and how recipients
understand probability phrases featuring ``I'' and ``it''. Our
hypotheses were derived from the model described by Kahneman and
Tversky (1982) and supported by data from Løhre and Teigen (2016)
showing that the pronoun is a marker of the source of uncertainty on
the internal-external continuum. Building on this account, probability
phrases featuring a first person pronoun subject are labelled
\textit{internal probability phrases }and probability phrases
featuring a third person neuter pronoun are labelled \textit{external
  probability phrases}.

Our materials were composed of the phrases featuring only probability
terms derived from the root \textit{certain} (e.g., \textit{very
uncertain}, \textit{uncertain}, \textit{not certain}, \textit{very
certain}, etc…). This was a strategic choice because the lemma
\textit{certain} is used with both first and neuter third person
pronouns and can be used to convey a large range of probability
magnitudes from around 30\% to 100\% (Bryant \& Norman, 1980; Reyna,
1981). Other confidence terms such as \textit{confident},
\textit{think} or \textit{believe} do not offer the same flexibility
and can be used only with an animated subject (\textit{Donald} thinks
that…, \textit{the mouse} believes the cheese is here). Likelihood
terms such as \textit{chance} can also convey a range of probabilities
but can only be used with inanimate subjects described with dummy
pronouns or nominal phrases (e.g., \textit{there} is a chance that it
will rain). We also chose not to mix words with numbers because
uncertainty words are considered as more natural (Wallsten, Budescu,
Zwick \& Kemp, 1993), and are expected to be more flexible and to
better reflect the way in which people feel uncertain than numbers
(Zimmer, 1986).

\subsection{Speakers’ experiments}

The two following experiments tested the factors driving speakers’
preferences for communicating internal and external probability
phrases. We aimed (1) to replicate past findings of Fox and Malle
(1997) regarding the expertise of the speaker and likelihood of the
event without confounded variables, (2) to test previously untested
theoretical propositions (e.g., that the time location of the uncertain
event affects the source of uncertainty; Kahneman \& Tversky, 1982),
and (3) to explore the effect of conversational dynamics (e.g.,
agreeing vs.\ disagreeing) on the preference for internal and external
probability phrases. 

\section{Experiment 1}

Given that uncertainty for past outcomes relies more on internal
uncertainty, we hypothesized that people would prefer internal
probability phrases (“I” probability phrases) when describing past
outcomes (vs.\ present and future outcomes). Further, building on Fox
and Malle’s (1997) findings, we expected that participants would prefer
to communicate higher probabilities with internal phrases, and medium
or low probabilities with external phrases. Regarding the
conversational context, our assumption was that contradicting a person
is face-threatening (Brown \& Levinson, 1987), which could be softened
by the use of an internal probability phrase (i.e., belonging to the
person). In contrast, we expected participants to prefer external
probability phrases, as reflecting a more objective reality (i.e.,
belonging to the world) when confirming a previously voiced opinion to
strengthen the effect of the agreement. Finally, given that internal
probability phrases can be taken as more subjective, we expected a
lower perceived disagreement between two internal probability phrases
than between two external probability phrases. 

\subsection{Method and results}

\paragraph{Participants} Overall 212 participants from Amazon
Mechanical Turk took part in the survey. Amazon Mechanical Turk is
considered as a reliable source of participants in psychology
(Buhrmester, Kwang \& Gosling, 2011; Paolacci, Chandler \& Ipeirotis,
2010). Participants’ age ranged from 18 to 67 (\textit{M} = 34,
\textit{SD }= 13), mostly Caucasian Americans (78\%), women (57\%),
employed (70\%), with some College education (87\%).

\paragraph{Stimuli and Procedure.} Participants were informed that the goal
of the study was to investigate their preference for internal
(\textit{I am} \textit{not certain}) or external (\textit{It is}
\textit{not certain}) probability phrases in uncertainty communication.
All questionnaires contained five selection tasks, presented in random
order for each participant, in which participants were instructed to
choose the sentence that was most appropriate in a list of two or four
sentences. 

\paragraph{Task 1: Outcome date.} Participants communicated a risk
associated with an outcome that happens either in the past, present or
future. In a between-subjects design, participants described the risk
related to a drug which was either produced in the past (\textit{drugs
that were produced in the Nineties}), in the present (\textit{drugs
that are produced now}) or in the future (\textit{drugs that will be
produced in the future}). Participants communicated the risk by
selecting one among four probability phrases. The four phrases resulted
from the crossing of two degrees of certainty (i.e., \textit{not
certain} and \textit{quite certain}) and two sources of uncertainty
(i.e., \textit{I am} vs.\ \textit{It is}). 
\begin{itemize}
\item ``I am not certain that drugs that were produced in
the Nineties were harmless.''
\item ``It is not certain that drugs that were produced in
the Nineties were harmless.''
\item ``I am quite certain that drugs that were produced in
the Nineties were harmless.''
\item ``It is quite certain that drugs that were produced
in the Nineties were harmless.'' 
\end{itemize}
Participants could choose one of four phrases, two internal and two
external. For the analysis, we summed the rate of selection of internal
and external phrases.

\paragraph{Task 1 Results.} Overall, to describe harmfulness of drugs,
participants had a slight preference for internal probability phrases
(``I am'', 54.7\%). They chose internal phrases more often to describe
the present risk of harm (63.2\%) than to describe the same risk
located in the past (52.5\%) or in the future (48.4\%), but
these differences were not statistically significant ($\chi^2$(2,
\textit{N} = 212) = 3.17, \textit{p} = .205, $\phi = .12$).

\paragraph{Task 2: Dice probability scenario.}
Participants were asked to select a phrase to express a medium or a
high probability of a specific outcome in a dice roll: a 50\% probable
outcome (obtaining a score above 3: 4, 5 or 6), or an 83\% probability
(obtaining a score higher than 1: 2, 3, 4, 5 or 6).  They selected one
among four probability phrases taken from Task 1: I am/It is not
certain and I am/It is quite certain. The four phrases resulted from
the crossing of two degrees of certainty (i.e., \textit{uncertain }and
\textit{quite certain}) and two sources of uncertainty (i.e.,
\textit{I am} vs.  \textit{It is}). Participants could choose one of
four phrases, two internal and two external. For the analysis, we
summed the rate of selection of internal and external phrases.

\paragraph{Task 2 Results.} Overall, to describe the probability
of obtaining a given score with a die, half of the participants
selected an internal probability phrase (48.8\%) and the other half
selected an external one. In line with our hypothesis, participants
selected more internal probability phrases to describe the high
probability outcome (60.6\%) than to describe the medium probability
outcome (39.8\%; $\chi^2$(1, \textit{N} = 212) = 9.13,
\textit{p} = .003, $\phi = --.21$).

\paragraph{Task 3: Contradiction scenario}. Participants played the
role of Speaker 2 in a dialogue between Speaker 1 and Speaker 2 about
the chances of Laura passing her exam. The vignette was designed using
a 2 (Contradiction trend: Speaker 2 was less certain vs.\ more
certain) × 2 (Source of uncertainty used by Speaker 1: internal vs.\
external) between-subjects design. The second speaker (the
participant) was either \textit{less} certain (Speaker 1: certain –
Speaker 2: not certain) or \textit{more} certain than Speaker 1
(Speaker 1: not certain – Speaker 2: certain). Further, Speaker 1 was
either voicing an external or an internal probability
phrase. Participants took the role of Speaker 2 and had to choose to
use an internal or an external probability phrase to respond to
Speaker 1.

In the less certain contradiction condition, participants read the
following in the internal source for Speaker 1 condition. The text
between brackets shows the equivalent in the external source condition:

\medskip
\noindent
{\itshape
Select the response that sounds the most appropriate. ~ }

Speaker 1: - ``I am [It is] certain that Laura will pass
her exam''. ~

Speaker 2: 

$\bullet$ ``No, it is not certain''.

$\bullet$ ``No, I am not certain''.
\medskip

In the more certain contradiction condition, participants read the
following:

\medskip
Speaker 1: - ``I am [It is] not certain that Laura will
pass her exam''.

Speaker 2: 

$\bullet$ ``No, it is certain''.

$\bullet$ ``No, I am certain''.

\paragraph{Task 3: Results.} To voice a contradiction,
participants overall slightly preferred external probability phrases
(54.7\%). To test the effect of the direction of the contradiction
(more certain vs.\ less certain) and of the pronoun used by the first
speaker, we conducted a logistic regression with the two factors as the
independent variable and the source of uncertainty of the phrase chosen
as the dependent variable (\textit{I am} vs.\ \textit{It is}). The
regression model predicted correctly 67.5\% of the
cases ($\chi^2$(2, \textit{N} = 212) = 29.76, \textit{p}
{\textless} .001, Cox and Snell $R^2$ = .13). 

Participants selected more often an external probability phrase when
they were less certain than Speaker 1 (certain $\to$ it is uncertain;
58.9\%) than when they were more certain than Speaker 1 (uncertain
$\to$ it is certain; 50\%; B(\textit{df} = 1) = --0.64, \textit{SE}
= 0.31, \textit{p} = .038, OR = 0.53, 95\% CI [0.29, 0.96]). Further,
participants were more likely to mirror the source of uncertainty
selected by their conversational partners (B (\textit{df} = 1) = 1.55,
\textit{SE} = 0.31, \textit{p} {\textless} .001, OR = 4.73, 95\% CI
[2.59, 8.62]). When the first speaker uttered an internal probability
phrase, participants were more likely to respond with an internal
probability phrase too (64.2\%), and similarly, when the first speaker
uttered an external probability phrase, participants also responded
with an external probability phrase (70.1\%).

\paragraph{Task 4: Confirmation scenario.} Participants
read a dialogue between two conversational partners (Speaker 1 and
Speaker 2) discussing the chances of Denis passing his driving license.
In a 2 (Probability magnitude: medium vs.\ high) × 2 (Source of
uncertainty: internal vs.\ external uncertainty) between-subjects
design, Speaker 1 conveyed either a medium or high probability (i.e.,
\textit{not certain }vs.\ \textit{certain}), using either an internal or
an external probability phrase (\textit{I am} vs.\ \textit{It is}).
Participants chose the most appropriate probability phrase for the
second conversational partner.

For instance, in the medium probability condition, participants read the
following:

\medskip
Speaker 1: ``I am [It is] not certain that Denis will
pass his driving licence''.

Speaker 2: ``Yes, it is not certain''

Speaker 2: ``Yes, I am not certain''

\medskip\noindent
In the high probability condition, participants read the following:

Speaker 1: ``I am [It is] certain that Denis will pass
his driving licence''. ~

Speaker 2: ``Yes, it is certain''

Speaker 2: ``Yes, I am certain''

\paragraph{Task 4: Results.} Overall, to voice a confirmation,
participants used more often external probability phrases (61.3\%). To
test for the main effect of the probability conveyed and of the marker
of the source used by Speaker 1, we conducted a logistic regression
with the probability magnitude and the source of Speaker 1 as
independent variables and the choice of the marker of the source by
participants as the dependent variable. The regression model predicted
correctly 70.3\% of the cases ($\chi^2$(2, \textit{N} = 212) = 30.99,
\textit{p} {\textless} .001, Cox and Snell $R^2$ = .14).

As expected, and as in the dice scenario, participants used an internal
probability phrase more often to convey a high probability than to
convey a medium probability (49.1\% vs.\ 26.5\%; B (\textit{df} = 1) =
--0.85, \textit{SE} = 0.31, \textit{p} =.006, OR = 0.43, 95\% CI [0.23,
0.78]).

Further, as in the contradiction scenario, participants mirrored the
source of uncertainty of their conversational partner. When the first
speaker used an internal probability phrase, participants preferred an
internal probability phrase (55.4\%), whereas when the first speaker
used an external probability phrase, most participants preferred
answering with an external probability phrase (76.6\%; B (\textit{df} =
1) = 1.32, \textit{SE} = 0.31, \textit{p} {\textless} .001, OR = 3.73,
95\% CI [2.05, 6.81]).

\paragraph{Task 5: Level of disagreement between predictions.}
Participants read two rain forecasts broadcast by two different TV
channels. Both forecasts featured the same source of uncertainty but
conveyed a different probability magnitude. Participants judged the
extent to which the forecasters disagreed on a 5-point Likert scale
ranging from 1: \textit{Not at all }to 5: \textit{Completely}.
\begin{itemize}
\item ``I am [It is] certain that it will rain.''
\item ``I am [It is] uncertain that it will rain.''
\end{itemize}

\paragraph{Task 5: Results.} Overall, participants rated that the
two weather forecasters, who made different probabilistic forecasts
using the same marker of the source, disagreed (\textit{M} = 3.66,
\textit{SD} = 1.16 on a 5-point scale ranging from \textit{Not at all}
to C\textit{ompletely}). However, the markers of the source in the
probability phrases did not have an effect on participants’ perception
of the level of disagreement between the weather forecasters
(\textit{M}\textsubscript{Internal} = 3.70, \textit{SD}
= 1.22 and \textit{M}\textsubscript{External} = 3.64, \textit{SD} =
1.12, \textit{t} (210) = 0.37, \textit{p} = .710, \textit{d} = 0.05). 

\subsection{Discussion}

In the five scenarios, participants chose a different pronoun subject as
a function of the probability of occurrence of the outcome and the
conversational situation. Participants used more internal probability
phrases to express high probabilities than to express medium
probabilities. The effect of the probability magnitude on the
preference for specific phrase subjects does not exactly match the view
that the pronoun is a marker of the source or subjectivity, given that
any dice outcome could be considered as equally objective and stemming
from aleatory uncertainty.

Participants did not have different subject preferences for outcomes
that are typically frequency based and considered objective (e.g., the
outcome of a dice roll) and outcomes that are less distributional and
more subjective (whether drugs can be harmful) – the average was around
50\% for both. This does not support the hypothesis that the subject
marks the source of uncertainty nor the hypothesis that third person
pronouns mark objectivity (Fox \& Ülkümen, 2017). Interestingly, when
set in a conversation, participants preferred to convey the same source
of uncertainty as their conversational partners, whether they agreed
with or contradicted that person.

Our data did not show that the timing of an outcome would affect the
preference of markers of the source of uncertainty. This appears to
contrast with previous findings that the time of occurrence of
an outcome is an important factor in determining the source of
uncertainty (Brun \& Teigen, 1990; Kahneman \& Tversky, 1982). Our
result complements the findings of Ülkümen et al.\ (2016) who found that
future outcomes were more often described with likelihood quantifiers,
albeit not after controlling for other aspects of the sentence (e.g.,
control, source). The next experiment aimed to further look into the
time of occurrence of an outcome in conjunction with the level of
knowledge regarding this outcome.

\section{Experiment 2}

\renewcommand{\baselinestretch}{1.02} \large\normalsize

We propose that knowledge is a key variable to explain the effect of
timing observed in past research (Brun \& Teigen, 1990; Kahneman \&
Tversky, 1982) and the lack of effect observed in Experiment 1. We
propose that the knowability of an outcome – whether one can assess
whether it will occur or not – is often confounded with the timing of
an event – predicts the preference for ``I'' vs.\ ``it'' sentences.

Uncertainty about past outcomes stems from a lack of personal knowledge because
whether the outcome has occurred or not is a fact that at least some
people \textit{know}. Uncertainty about future outcomes may stem from
a lack of knowledge but also from stochastic properties of the world
such that nobody knows \textit{for sure} what will happen. In our drug
scenario in Experiment 1, participants may not have experienced
variations in perceived knowledge regarding the outcome whether it was
past, present or future. Indeed, the time when the drug could be
dangerous and the degree of knowledge of participants regarding drugs
may not have been connected (e.g., strong knowledge of the
dangerousness of past drugs vs.\ lack of knowledge of the
dangerousness of future drugs). The timing of an event and its
knowability are independent dimensions that are negatively correlated
(more knowledge about past events) for some outcomes but not for some
others. There are instances where the opposite relationship exists: we
sometimes lack knowledge about past outcomes (e.g., whether
Shakespeare has or has not written King Lear) and we can be very
knowledgeable about future outcomes (e.g., when and where the moon
will rise in a week).

We propose that one of the mechanisms underlying the preference for
internal or external probability phrases relies on the knowledge of the
outcome and the instrumentality of this knowledge to assess
uncertainty. Building on the “knowability” dimensions proposed by Chow
and Sarin (2002), we investigated the preference for internal and
external probability phrases for known, predictable and unknowable
outcomes. We expected that participants would use more internal
probability phrases for known or predictable outcomes than for unknown
outcomes. 

\subsection{Method}

\paragraph{Participants.} One hundred and thirty-one students at a
Norwegian university took part in the survey. The socio-demographic
characteristics of this group were not recorded.

\paragraph{Materials and Procedure.}
We selected 10 outcomes (listed below) falling into three
categories: \textit{known }outcomes\textit{, predictable }outcomes and
\textit{unknowable }outcomes\textit{. Known }outcomes were defined as
either past agreed outcomes (e.g., the UN was founded after the war)
or current realities (e.g., Sweden won the last match against
Denmark). For \textit{known outcomes}, uncertainty is deemed only
internal because a quick search would enable people to reach
certainty. \textit{Predictable }outcomes were defined as future
outcomes for which uncertainty is both internal and external:
knowledge about the world helps to reduce uncertainty but cannot bring
certainty.  \textit{Unknowable }outcomes were defined as past, present
or future outcomes that are unknowable for certain, given the state of
knowledge of humanity. For those outcomes, there is no identified
point in time where the outcome will be fully certain. Uncertainty for
those outcomes relies further on external uncertainty because nobody
has a true knowledge of whether an event has happened or will happen.

For each outcome, participants selected one of two probability phrases
that appeared most natural to them between the phrase featuring ``I
am'' and the one featuring ``It is''. If they perceived both phrases
to be natural, participants were asked to select the one that sounded
most like a genuine quotation.

Participants selected a probability phrase for four known outcomes,
four predictable outcomes and two unknowable outcomes. The outcomes
were described with medium or high verbal probabilities which are
presented below between brackets. The four known outcomes were
composed of two historical events and two geographical facts: “The UN
was founded after the war” (\textit{almost certain}), “Sweden won
their last match against Denmark” (\textit{uncertain}), “Lithuania is
South of Latvia” (\textit{uncertain}), “Toulouse is in France”
(\textit{certain}). The four predictable outcomes were all located in
the future: “Spain will be part of the 2012 European Championships”
(\textit{quite certain})\footnote{ The data was collected in 2011,
  before participants could know who would take part in the 2012
  European Championships.}, “Sweden will win their next match against
Denmark” (\textit{uncertain}), “What I will do tomorrow” (\textit{not
  certain}), “Hans will accept the offer” (\textit{not certain}). The
two unknowable outcomes were: “There is life on other planets”
(\textit{quite certain}) and “Robin Hood has actually lived”
(\textit{not certain}).  Participants then completed an additional
task which is not reported here. The order of the question was fixed
as follows: UN, Spain, Sweden past match, Sweden future match, life on
other planets, Robin Hood, Lithuania, Toulouse, What I will do and
What Hans will do. The survey was in Norwegian and is presented in
English in the Appendix.

\renewcommand{\baselinestretch}{1.0} \large\normalsize

\begin{table*}[t]\centering
\caption{Preference for internal and external probability phrases (in \%)
along with a binomial test with a value of 50\%. “I” is a marker of
internal source of uncertainty and “It” is a marker of external source
of uncertainty.}
\begin{tabular}{L{1in}lccc}\toprule
 &  & \mc{2}{l}{Source of uncertainty} & \\\cmidrule{3-4}
Knowledge & Outcome & I am & It is & Binomial test\\\midrule
\multirow{4}{1in}{Known (past/current)} & UN – Almost certain & \bfseries 92.4 & 7.6 & \textit{p} {\textless} .001\\
 & Sweden – Uncertain & \bfseries 96.2 & 3.8 & \textit{p} {\textless} .001\\
 & Lithuania – Uncertain & \bfseries 95.4 & 4.6 & \textit{p} {\textless} .001\\
 & Toulouse – Certain & \bfseries 68.7 & 31.3 & \textit{p} {\textless} .001\\\cmidrule{2-5}
 & Total knowable  & \bfseries 88.2 & 11.8 & \\\midrule
\multirow{4}{1in}{Predictable (future)} & Spain - Quite certain & \bfseries 57.3 & 42.7 & \textit{p = }.115\\
 & Sweden – Uncertain & 37.7 & \bfseries 62.3 & \textit{p = }.006\\
 & What I will do - Not certain & \bfseries 95.4 & 4.6 & \textit{p} {\textless} .001\\
 & What Hans will do - Not certain & \bfseries 65.6 & 34.4 & \textit{p} {\textless}
.001\\\cmidrule{2-5}
 & Total predictable  & \bfseries 64.0 & 36.0 & \\\midrule
\multirow{2}{1in}{Unknowable} & Life on other planets - Quite certain & 48.9 & \bfseries 51.1 & \textit{p = }.861\\
 & Robin Hood - Not certain & 26.0 & \bfseries 74.0 & \textit{p} {\textless}
.001\\\cmidrule{2-5}
 & Total unknowable  & 37.4 & \bfseries 62.6 & \\\cmidrule{2-5}
 & \bfseries Grand Total & \bfseries 63.2 & 46.8 &  \\\bottomrule
\end{tabular}
\end{table*}

\subsection{Results and discussion}

As expected, participants selected more often an internal probability
phrase for known and predictable outcomes than for unknowable
outcomes.  To describe the four knowable outcomes, a large majority of
participants selected an internal probability phrase as more natural
than an external one (88\%, see Table 2). For predictable outcomes,
the preference for an internal or external source of uncertainty was
less strong, with three phrases out of four where participants
preferred the internal version, forming overall a smaller majority
(64\%). Regarding the future outcomes, one can also see that the
preference for the first person pronoun subject was stronger when the
statement was about the speaker and featured a first person
pronoun. The only item for which “it” was preferred among the future
outcome was for the future results of a Swedish football match. This
preference may have been the result of a contrast between this
question and the previous one that focused on the past result of the
Swedish team and for which participants largely preferred the “I”
prediction. This echoes findings of Experiment 1, showing a mirroring
effect in conversation. Finally, for unknowable outcomes (i.e., life
on other planets and Robin Hood), participants preferred external
probability phrases, although this preference was significantly
different from 50\% only for the Robin Hood sentence.

We computed a summation score of preference for internal probability
phrases within each outcome category (known, predictable and
unknowable outcomes), and we normalized this score by the total number
of sentences within the outcome category. Hence, each participant had
a score ranging from 0 to 1 for known, predictable and unknowable
outcomes, 0 representing a systematic preference for external
probability phrases and 1 a systematic preference for internal
probability phrases. We entered these three scores in a within-subject
(``repeated measures'') variance analysis with the type of outcome as
independent variable and the internal probability phrase score as
dependent. The type of outcome had a main effect on the preference for
internal probability phrases (\textit{F}(2,260) = 129.29, \textit{p}
{\textless} .001, $\eta^2_p$ = .50). Participants exhibited a stronger
preference for internal probability phrases for knowable outcomes than
for predictable outcomes and unknowable outcomes
(\textit{M}\textsubscript{Diff} = 0.32; 95\% \textit{CI }[0.26, 0.38],
\textit{p} {\textless} .001; and \textit{M}\textsubscript{Diff} =
0.51, \textit{CI} [0.43, 0.59], \textit{p} {\textless} .001),
respectively, and a stronger preference for internal probability
phrases for predictable outcomes than for unknowable outcomes
(\textit{M}\textsubscript{Diff} = 0.19, \textit{p} {\textless} .001,
CI [0.10, 0.27], pairwise comparisons with Bonferroni adjustment).

\subsection{Interim discussion}

Overall, the two experiments presented here complement and extend the
current literature in several respects. First, the knowability of an
outcome is a good predictor of the preference for internal and
external probability phrases. Participants preferred strongly internal
phrases for known outcomes – defined as established historical or
geographical facts – whereas this preference was less strong for
predictable outcomes and even the opposite for unknowable
outcomes. Second, speakers have a slight preference for internal
probability phrases (e.g., ``I am not certain''). However, this
preference depended – in addition to the knowability – on the
likelihood of occurrence of the outcome as well as the conversational
context. This general internal preference and the role of the
probability magnitude replicates prior findings (Fox \& Malle,
1997). Third, and more novel, participants tended to choose more often
a probability phrase that mirrored the source of uncertainty used by
their conversational partner (conversation vignettes in Experiment 1
and Personal future action phrase in Experiment 2).

Furthermore, results of Experiment 2 do not support the hypothesis
that the pronoun subject was chosen to mark the subjectivity of the
speaker (Fox \& Ülkümen, 2017; Ülkümen et al., 2016). Indeed, outcomes
characterized by the least amount of data or a lack of consensus and
whose probability was hence subjective (e.g., life on other planets),
were more often described with a third person neuter pronoun, which
was posited to mark objectivity. In contrast, outcomes for which facts
existed or are consensually agreed and whose probability was hence
more objective were mainly described with first person pronoun
phrases. These results are more in line with the hypothesis that the
subject of uncertainty phrases is primarily a marker of the source of
uncertainty (Teigen \& Løhre 2017).

Given that speakers use contextual cues to decide whether it is best to
say “I am uncertain” or “It is uncertain”, then we can assume that the
pronoun subject carries pragmatic implications for recipients. The
possibility that probability phrases convey pragmatic meanings (e.g.,
about the state of knowledge of speakers, about their intentions) is
not novel and falls within a literature strand positing that
probability phrases convey more than a vague probability magnitude to
recipients (Moxey \& Sanford, 2000; Teigen \& Brun, 2003). More
generally, the hypothesis that language has a strong pragmatic layer
fits a functional approach of language (Fiedler, 2008).

\subsection{Impact of linguistic markers of uncertainty sources on hearers}

There is little and mixed evidence about what recipients infer from
linguistic markers of the source of uncertainty. For example, in one article,
recipients inferred that speakers uttering internal probability phrases
were more knowledgeable than speakers uttering external probability
phrases in one study out of three; in the remaining two studies, the
mean differences were not statistically significant (Løhre \& Teigen,
2016; Experiment 1 vs.\ Experiment 3 and 4). Another example of mixed
results is related to the inference about the personal interest of the
speaker: in one study out of two, a first person pronoun was taken as a
cue of increased personal interest in comparison with a neuter subject
pronoun (Experiment 3 vs.\ Experiment 4). 

Previous research indicated that recipients may draw some inferences
from the use of internal and external probability phrases such as
speakers’ levels of knowledge or the nature of the evidence they used
(Fox \& Malle, 1997; Løhre \& Teigen, 2016; Ülkümen et al., 2016).
However, the pattern of inferences drawn in previous research was not
consistent. In Experiments 3 and 4, we assess the impact of internal
and external probability phrases on the recipients’ inferences and
their decisions. Experiments 3 and 4 aim to replicate and broaden
previous findings by showing that linguistic markers of the source of
uncertainty affect the judgments and decisions of recipients (Fox \&
Malle, 1997; Løhre \& Teigen, 2016; Ülkümen et al., 2016).

\section{Experiment 3}

We hypothesized that markers of the source of uncertainty used in
probability phrases would affect the recipients’ judgments about the
speaker as well as their subsequent decisions. This expectation is
consistent with prior research (Løhre \& Teigen, 2016). Specifically,
we expected that recipients would perceive speakers uttering an
external probability phrase as more knowledgeable and less supporting
of the outcome. We expected that recipients would interpret external
probability phrases as being based on outcome frequencies and as being
more informative than internal probability phrases. Finally, we
expected that recipients would be more likely to use external
probability phrases to guide hypothetical bets than internal
probability phrases. 

\subsection{Method}

\begin{table*}[t]\centering
\caption{Internal and external probability phrases used in Experiments 3 and 4.}
\begin{tabular}{ll}\toprule
Probability & Probability phrase\\\midrule
Low & ``I am [It is] very uncertain that VfL Bochum will win against
Hoffenheim.''\\
Moderate & ``I am [It is] not certain that Wolfsburg will win against FSV
Mayence.''\\
High & ``I am [It is] almost certain that Borussia Dortmund will win
against the Bayer Leverkusen.''\\\bottomrule
\end{tabular}
\end{table*}

\paragraph{Participants.} Overall 256 native French speakers took part in
the survey, recruited through a pool of participants interested in
cognition (RISC – Réseau d’Information Sur la Cognition). Participants
were between 19 and 69 years old (\textit{M} = 30.64, \textit{SD} =
10.47) and 66\% of them were women.

\paragraph{Design.} Hypotheses were tested in a 2 (Source of uncertainty:
internal vs.\ external) × 3 (Probability magnitude: low, medium, high)
mixed-design. The source of uncertainty was manipulated
between-subjects by the subject pronoun used in the prediction, either
“I” or “It”. The probability magnitude was manipulated
within-subject using three different verbal probabilities: \textit{very
uncertain}, \textit{not certain} and \textit{almost certain}. 

\paragraph{Materials and procedure.} Participants took part in the
questionnaire on the Internet (using the platform
LimeSurvey\textsuperscript{®}). Participants were asked to randomly
select one of two web-links to participate: the first link led to the
questionnaire featuring internal probability phrases and the second
link led to the questionnaire featuring external probability phrases.
Participants were instructed to pay attention before validating their
answers, as they could not go back.

Participants judged three football game predictions made by Leo (a
French person randomly selected as part of a survey on football
knowledge). The three predictions featured different probability
magnitudes and focused on different hypothetical matches in the German
league: Match 1, VfL Bochum vs.\ Hoffenheim; Match 2, Wolfsburg~vs.\ FSV
Mayence; Match 3, Borussia Dortmund vs.\ the Bayer Leverkusen. The same
pairs were used for all participants. The first team of each pair was
predicted as having a low, moderate and high probability of winning,
respectively. The probability magnitude of winning was manipulated by
using a verbal probability reflecting a low, moderate or high
probability as shown in Table 3.

The order of presentation of the probability phrases was either from low
to high probability magnitude or from high to low. The pairs of teams
and their associated probabilities of wining were selected randomly in
the German Champions’ league. 

For each football game prediction, participants answered five
questions.  Participants assessed the speaker’s knowledge of the two
teams and whether he supported the team concerned with the prediction.
Participants also assessed the extent to which the prediction was
based on statistical information and informativeness. Finally,
participants assessed their willingness to use the information if they
were to bet on the game. Questions were presented in a fixed order:
knowledge of the speaker, prediction based on statistics, use of the
prediction if betting, informativeness of the prediction, and team
preference of the speaker. Participants provided their judgments on
5-point Likert scales. On a new webpage, as a manipulation check for
the probability manipulation, participants were subsequently reminded
of each prediction and assessed the probability conveyed by Leo on an
11-point scale ranging from 0: ``Leo is certain that the team will not
win'' to 10: ``Leo is certain that the team will win''.  Finally,
participants provided their age, gender, job, and mother tongue, and
their subjective level of expertise in the German Champions Football
League (scale from 1: \textit{No knowledge at all} to 5:
\textit{Expert about this Championship}).

\subsection{Results}

\begin{figure*}[t!]
\includegraphics[width=3.2in]{fig1a.eps}\qquad%
\includegraphics[width=3.2in]{fig1b.eps}\medskip

\begin{center}
\includegraphics[width=3.2in]{fig1c.eps}
\end{center}
\caption{Mean judgments provided for three football game
  predictions as a function of the sentence subject (``I'' vs.\
  ``it''), Experiment 3. Judgments focus on the speaker’s knowledge and support, on
  the data used in the prediction, the prediction informativeness and
  about participants’ willingness to use the prediction in
  betting. Error bars are 95\% confidence intervals.}

\textit{Note:} All judgments used a 5-point scale ranging from 1:
\textit{Not at all} to 5: \textit{Completely}. High probability of
winning: Borussia Dortmund vs. the Bayer Leverkusen; Moderate
probability of winning: Wolfsburg vs. FSV Mayence and low probability of winning: VfL Bochum vs.
Hoffenheim.
\end{figure*}

\paragraph{Manipulation checks.} The expertise of participants in the
German league was relatively low (\textit{M} = 1.21, \textit{SD} =
0.60, on a scale ranging from 1 to 5) and did not affect the dependent
variables nor interact with the independent variables. The expertise
was therefore not included in the analyses described below. 

We checked whether the manipulation of the probability magnitude was
effective by comparing participants’ probability perception in the
different probability magnitude conditions. Further, we tested whether
the source of uncertainty (``I'' vs.\ ``It'') affected the probability
perceived by participants, as this could suggest that the effect of
the source could be indirect through probability perception. We
conducted a mixed design variance analysis with probability magnitude
and source as independent variables and probability perception as
dependent variable. The probability magnitude manipulation was
successful. The probability perception was low for \textit{very
  uncertain} predictions 3.22 (\textit{SD} = 2.48), moderate for
\textit{not certain} 4.34 (\textit{SD} = 1.71) and high for
\textit{almost certain} 7.67 (\textit{SD} = 1.43; 11-point scale
ranging from \textit{certain that the team will not win} to
\textit{certain that the team will win}; and \textit{F}(1.67,425.12)
= 375.99, \textit{p} {\textless} .001, $\eta^2_p$ = .60). Furthermore,
and importantly, the source of uncertainty did not have a main effect
or an interaction effect with probability magnitude on probability
perception, \textit{Fs} {\textless} 1. Therefore, internal and
external probability phrases were perceived as conveying the same
levels of probability.

\paragraph{Effects of source of uncertainty and probability
  magnitude.}

Figure 1 illustrates all results. For each of the dependent variables
(other than probability), we asked whether the mean response was
dependent on the source (``I'' vs.\ ``It'') with a between-group
t-test. We also assessed the effect of probability on each variable by
subtracting the low-probability case from the high-probability case,
for each subject. All dependent variables except the variable Use of statistics
yielded higher ratings with higher probabilities ($p<.001$ for each of
the four).

Speakers were judged as more knowledgeable when they used an external
probability phrase (``It'') than when they used an internal phrase,
but this difference was not significant ($t\, (240.15) = 1.29$, n.s.,
Welch corrected). But the high-low probability difference also
differed as a function of source ($t\, (253.45) = 2.25$, $p=.025$). As is
apparent in Figure 1, the effect of source was present only for the
two highest probabilities. The resulte for usefulness in betting were
similar ($t\, (247.71) =1.75$ for the main effect, $t\, (226.89) =4.03$,
$p<.001$, for the high-low difference).

The source did not make a difference in terms of team
support. External probability phrases were perceived to be more often
based on statistics ($t\, (216.5)=2.65$, $p=.001$) and to be more
informative($t\, (253.14) =3.62$, $p<.001$).

The results of the present experiment illustrate that recipients can
draw inferences from the pronoun subject used in a
prediction. Participants use the grammatical subjects of probability
phrases to draw inferences about the prediction and its speaker. These
inferences are consistent with the assumption that the grammatical
subject of a probability phrase is a marker of a speaker’s source of
uncertainty and that the source of uncertainty conveyed has
psychological implications for the hearer. For example, participants
perceived an external probability phrase as more statistically based
and more informative than internal probability phrases.

These results highlight that participants infer that speakers using a
neuter third person pronoun rely more on an external source of
uncertainty. The sentence subject was also related to perception of
subjectivity, but this effect was dependent on the strength of the
belief conveyed by the speaker. The judgments of informativeness and
willingness to use in betting depended on both the grammatical subject
and the probability conveyed.  In the next experiment, we assessed the
role of the expertise of the speaker by manipulating it. Further, we
improved the design by randomizing the order of the predictions and of
the questions.

\section{Experiment 4}

Experiment 4 tests further the effect of the source of uncertainty
communicated on judgment and decision-making. We replicated the
uncertainty source manipulation and extended Experiment 3 by
manipulating the expertise of the speaker. In this experiment,
participants drew inferences about the perceived knowledge of the
speaker, his perceived support and the kind of information that the
prediction relies on (e.g., information about past matches). In
addition, participants focused on the perceived processes of forming
predictions (e.g., intuition), assessed judgments about the speaker’s
attitude toward the betting situation (e.g., encouraging or not) and
focused on potential consequences for the speaker (e.g.,
responsibility, correctness). 

We derived hypotheses based on existing empirical evidence showing that
participants preferred to use internal probability phrases made by
experts. This was related with the perception that experts “took
responsibility” in their prediction by using a first person pronoun. In
contrast, participants preferred to use the external probability
phrases of novices, which they felt reflected a greater responsibility
than internal probability phrases (Fox \& Malle, 1997). We hypothesized
that novice speakers uttering an external probability phrase would be
judged as more knowledgeable, less supportive of the team and less
encouraging, but also less wrong and blameworthy if the team lost, than
speakers uttering internal probability phrases. We expected the results
to be mirrored for expert speakers.

\subsection{Method}

\paragraph{Participants.} 

Overall 81 Psychology students from Birmingham University took part in
the survey, mostly female (80\%). Participants’ ages ranged from 18 to
24 (\textit{M} = 18.94, \textit{SD} = 1.03). 

\paragraph{Design.} We employed a 2 (Uncertainty source: internal vs.
external) × 2 (Expertise: novice vs.\ expert) × 2 (Probability
magnitude: very uncertain vs.\ almost certain) mixed design. The first
two factors were manipulated between-subjects, whereas probability
magnitude was manipulated within-subject. Thus, each participant read
two out of eight possible predictions.

\paragraph{Materials and procedure.} The source of uncertainty was
manipulated as in Experiment 3 (i.e., \textit{I am }or \textit{It is
}preceded the prediction). Expertise was manipulated by presenting the
speaker (i.e., Miro) as having either a very limited experience of the
league (novice speaker; i.e., “He has watched some of the champion
league matches 5 years ago and has never read any magazines on
football”), or an extensive experience (expert speaker; i.e., “He has
watched all the champion league matches of the last 5 years and he
reads different magazines on football”). Each participant assessed two
predictions, one conveying a low probability (\textit{It} \textit{is [I
am] very uncertain that FC Nitra will win against FC Senec}) and one
conveying a high probability (\textit{It is [I am] almost certain that
ZTS Dubnica will win against Spartak Trnava}). The order of
presentation of the two predictions was randomized.

After reading Miro's prediction, participants judged to
what extent: (1) Miro has knowledge about these teams; (2) Miro is
supporting FC Nitra; (3) Miro would be wrong in the case where FC Nitra
does not win against FC Senec; (4) Miro could be blamed if one bets and
loses; (5) the prediction could be seen as an encouragement to bet on
FC Nitra; (6) the prediction relies on the results of previous matches;
(7) the prediction relies on intuition. Then, participants assessed
whether they would bet on the team in question. The order of
presentation of the questions was randomized for each participant. All
the judgments were provided on a 5-point Likert scale ranging from 1:
\textit{Not at all}, to 5: \textit{Very much}. Finally, participants
assessed the probability conveyed by Miro for the two predictions.
Participants were given the two predictions that they had judged,
finished by “because”. The answer to this question was not analysed as
part of the present paper. Finally, participants provided their
socio-demographic details.

\subsection{Results}

\begin{figure*}[t!]\centering
\includegraphics[width=3.2in]{fig2a.eps}\qquad%
\includegraphics[width=3.2in]{fig2b.eps}\medskip

\includegraphics[width=3.2in]{fig2c.eps}\qquad%
\includegraphics[width=3.2in]{fig2d.eps}
\caption{Effect of expertise and source of uncertainty on
judgments about recipients’ inferences for low and high probability
phrases (\textit{N} = 81), Experiment 4. Judgments were given on a 5-point Likert
scale ranging from 1: \textit{Not at all }to 5:
\textit{Completely}. Error bars are 95\% confidence intervals.}

\end{figure*}

\renewcommand{\baselinestretch}{1.05} \large\normalsize

\paragraph{Manipulation check.} 

We tested whether the manipulation of the probability was effective and
whether the source of uncertainty and the speaker’s expertise affected
the perceived probability of participants, as this could suggest that
the effects of the independent variables were due to an indirect effect
through probability perception. We conducted a mixed design variance
analysis with probability magnitude, source, and expertise as
independent variables and probability perception as dependent variable.
The probability magnitude manipulation was successful: participants
perceived the probability phrase featuring \textit{almost certain} as
conveying a high probability (\textit{M} = 7.67, \textit{SD} = 1.43;
and \textit{very uncertain} as conveying a low probability (\textit{M}
= 3.22, \textit{SD} = 2.48), \textit{F}(1,77) = 266.47, \textit{p}
{\textless} .001, $\eta^2_p$ = .78). Furthermore,
and importantly, the source of uncertainty and the expertise of the
speaker did not have a main effect or an interaction effect on
probability perception, \textit{Fs} {\textless} 1. Therefore, internal
and external probability phrases were perceived as conveying the same
level of probability. 

\renewcommand{\baselinestretch}{1.07} \large\normalsize

\paragraph{Effects of the uncertainty source, expertise and
  probability magnitude.} Figure 2 shows the mean responses as a
function of the source of uncertainty, probability conveyed and
expertise of the speaker. We analyzed the effects on each response
using t-tests as in Experiment 3. The probability manipulation
affected all measures at $p<.001$ except for Frequency, Intuition, and
Knowledge, where effects were not significant even at $p<.05$. Aside
from this effect, the Wrong measure was not affected by any
manipulation, so is not discussed further. Likewise, the source
manipulation (``I'' vs.\ ``It'') and the expertise manipulation did
not have an overall main effect on any measure (although Willingness
to bet and Know were almost significantly higher with higher
expertise, $p=.07$ for both).

\renewcommand{\baselinestretch}{1.0} \large\normalsize

The main result of interest is that the interaction between expertise
and source was significant for Encouragement, Support, and Know (with
respective p-values of .011, .026, and .011) and almost significant for
Willingness to bet (\textit{p}=.0723). In all cases, ratings were higher when
experts used ``I'' and when non-experts used ``It''.  The interaction
effects reflect that participants judged an expert uttering an
internal probability phrase as more knowledgeable and more encouraging
than an expert uttering an external probability phrase, whereas they
considered the opposite was true of a novice: a non-expert using an
internal probability phrase rather than an external one is seen as
more knowledgeable and more encouraging. Similarly, experts were
perceived to be more supportive of the team when producing an internal
probability phrase than when producing an external probability phrase,
whereas non-experts were judged more supportive when uttering an
external probability phrase. Finally, participants were keener to bet
on the team when experts used an internal probability phrase than an
external one, but were keener to bet on an external prediction made by
a novice.\footnote{This interaction for Support was significantly
  greater when probability was high ($p=.016$ for this ``triple
  interaction'') but was not significant for any other measure.}

\begin{table}[t]\centering
\caption{Summary of the effect of the main factors: source of uncertainty,
probability magnitude and expertise on judgments in Experiments 3 (2
Source * 3 Probability, mixed-design) and 4 (2 Source * 2 Expertise * 2
Probability, mixed-design).}
\begin{tabular}{@{}l@{}C{.7in}C{.7in}C{.7in}@{}}\toprule
 & Source & Source * Probability & Source * Expertise\\\midrule
\bfseries Experiment 3 & & & \\
Knowledge           & No  & Yes & {}-{}-\\
Support             & No  & No & {}-{}-\\
Based on statistics & Yes & No & {}-{}-\\
Informativeness     & Yes & No & {}-{}-\\
Use if betting      & No  & Yes & {}-{}-\\\midrule
\bfseries Experiment 4  & & & \\
Knowledge          & No &  No & Yes\\
Support            & No &  No & Yes\\
Wrongness          & No &  No & No\\
Blame              & No &  No & No\\
Encouragement      & No & Yes & Yes\\
Frequency          & No &  No & No\\
Intuition          & No &  No & No\\
Willingness to bet & No & Yes & Almost \\\bottomrule
\end{tabular}
\end{table}

Table 4 offers a bird’s eye view of the results of Experiments 3 and
4.\footnote{As shown in the table but not mentioned before,
  Encouragement and Willingness to bet in Experiment 4 were affected
  by the probability manipulation (p-values of .001 and .042,
  respectively).}  The inferences drawn from the subject pronoun are
consistent with the hypothesis that it reflects the source. The effect
of the subject varied as a function of the probability conveyed and of
the level of expertise of the speaker. The results show that
recipients use the phrase subject and the expertise of the speaker
together to draw inferences about the knowledge and attitude of the
speaker, as well as to assess the persuasiveness of the
message. Therefore, to maximize communication impact, experts should
use internal markers of uncertainty (\textit{I am} certain that...),
whereas novices should use external linguistic markers of uncertainty.

\section{General discussion}

Thirty-four years ago, Kahneman and Tversky (1982) described four
variants of uncertainty and posited that those variants were connected
with specific lexical preferences in uncertainty communication. They
provided tentative definitions of the variants of uncertainty and some
compelling examples of linguistic markers of the source (e.g.,
\textit{the} probability is vs.\ \textit{my} probability is…). It is
only recently that the role of the source of uncertainty and its
representation in language has been more systematically tested (Fox \&
Ülkümen, 2017; Løhre \& Teigen, 2016; Ülkümen et al., 2016). However,
there is currently a debate over what is actually marking the source
of uncertainty in uncertainty language. Researchers have used the
examples provided by Kahneman and Tversky (1982) differently: some
have focused on the subject of the phrase and some on the probability
term being used. Unsurprisingly, the theoretical account of
researchers focusing on the probability terms posited that only the
probability term was a marker of the source, and that the subject was
a marker of subjectivity (Fox \& Ülkümen, 2017). In contrast, the
account of researchers focusing on the sentence subject posited that
the subject was a better marker of the source (Teigen \& Løhre
2017). The work presented here assumed that the pronoun subject of
probability phrases was used as a marker of the source of uncertainty
as hypothesised by Kahneman and Tversky (1982) and substantiated by
Løhre \& Teigen (2016).  Furthermore, this account also posits a
positive relationship between internal-external source of uncertainty
and the level of objectivity of a speaker. We aimed to test the
determinants and consequences of the use of pronoun subjects as
markers of the source of uncertainty.

Our results indicate that speakers use pronouns to mark the source of
the uncertainty. They also indirectly indicate that speakers use
pronouns primarily to mark the subjectivity of the source of their
uncertainty, but for recipients, the pronoun may be used to infer both
the source of uncertainty and the subjectivity of the speaker. For
example, speakers selected more often the “I” prediction for more
knowable outcomes (more objective), whereas unknowable outcomes
(subjective in nature) were more often described with the neuter
pronoun “It” (Experiment 2). In contrast, in the recipients’ studies,
both the source of uncertainty and the subjectivity of the speaker
could explain our pattern of results. For example, we could describe
the results of Experiment 4 as follows: “experts providing prediction
based on internal knowledge are more convincing than experts providing
predictions based on external information”, but also as follows:
“experts providing a subjective prediction are more convincing than
experts providing an objective prediction”. Future research designed
to test the different accounts of uncertainty markers would provide
more solid evidence.

Results also point to new determinants and consequences of the sentence
subject. In terms of determinants of sentence subjects, we found that
circumstantial factors, such as the probability of occurrence of the
outcome or the subject used by a conversational partner predicted the
preference for a specific pronoun subject (Experiment 1).
Interestingly, those factors were not related to the source of
uncertainty, nor to its subjectivity. Regarding novel effects of the
sentence subject, we found that the sentence subject affected people’s
willingness to use the prediction if betting (Experiments 3 and 4).
This indicates that the sentence subject may also be a pragmatic signal
of the course of action recommended by the speaker. In line with this
argument, participants also felt that the sentence subject was related
to the level of encouragement to bet of the speaker (Experiment 4).
Altogether, these findings indicate that the sentence subject has
several semantic and pragmatic functions: it is not only used by
recipients to infer the source of uncertainty, or the subjectivity of
the speaker.

\subsection{Theoretical update for linguistic markers of the source of uncertainty}

Our approach to uncertainty language is that it is like a tool box from
which speakers draw different tools that they use in a creative and
goal oriented way. Building on previous accounts of the language of
uncertainty (Fox \& Ülkümen, 2017; Teigen \& Løhre 2017) and the
present results, we propose that the subject and the probability term
mark the same qualitative information – the source of uncertainty – and
that they combine to create different quantitative levels of
internality or externality. In line with this account, data suggest
that the nature of the subject and the type of probability term have
been shown to correlate in a corpus of natural language (Ülkümen et
al., 2016). The rules for combining the added value of different
markers of the source could be simple, such as a basic addition
(internal pronoun + internal term = very internal) or could be more
driven by the subject, as suggested by (Løhre \& Teigen, 2016; Teigen
\& Løhre 2017).

We also propose that linguistic markers of the source have consequences
for the subjectivity perception of recipients. Our position is that
recipients infer the level of subjectivity of speakers based on their
source of uncertainty, together with the characteristics of the context
(e.g., who is speaking, in which context, about which outcome). This
model emphasizes the importance of the context, similarly to the model
proposed by Fox and Irwin (1998). In our model, the source of
uncertainty and the subjectivity are not psychologically independent
given that the source of uncertainty is a determinant of subjectivity.
The interaction effects found in Experiment 1 (with probability
conveyed) and in Experiment 4 (with probability conveyed and the
expertise of the speaker) support the view that the sentence subject of
probability phrases does not translate directly into a level of
subjectivity. 

Finally, our account posits that the source is a sufficient condition to
trigger the use of different sentence subjects, but also acknowledges
that it is not the only factor shaping this preference. Our model
embraces that the sentence subject could be used to indicate other
things than the source of uncertainty, including simply and directly
the subjectivity of the speaker. 

\subsection{Insight into how speakers choose internal and external probability
phrases}

Overall, our data suggest that the nature of the outcome and the context
in which it is predicted drive the preference for internal and external
probability phrases. 

\paragraph{Preference for internal probability phrases to convey high
likelihood.} Participants preferred to describe outcomes that were more
likely with internal probability phrases. This was for example the case
when they described the output of the cast of a die (Experiment 1).
Participants preferred to say “I am quite certain” than “It is quite
certain” but would rather say “It is not certain” than “I am not
certain”. The preference for internal probability phrases is consistent
with Fox and Malle’s (1997) findings, who showed similarly that high
numerical probabilities were more often introduced with the internal
probability term \textit{confidence} (“I am X\% confident”) and low
numerical probabilities with the external probability term
\textit{probability}. The preference to convey high probabilities with
the first person pronoun also fits well with the idea that more
knowledgeable speakers prefer to use an internal source of uncertainty
(Fox \& Malle, 1997), and the fact that a lower degree of internal
certainty is enough for participants to use a prediction (Løhre \& Teigen, 2016).

The preference for internal high probability phrases and external low
probability phrases observed in our experiment is limited to low
negative probability phrases and high positive probability phrases. In
our design, the lower probability phrases were also negative (i.e.,
\textit{uncertain, not certain}) whereas the high probability phrase
was positive (i.e., \textit{quite certain}). Hence, the preference for
the external source could have been driven by the negative
directionality of the lower probability phrases, and the preference
for the internal source by the positive directionality of the high
probability phrases. Negative probability phrases attract the
recipients’ attention towards the possibility that the target outcome
will not occur (Juanchich, Teigen \& Villejoubert, 2010; Sher \&
McKenzie, 2006). Using a first person pronoun negative directionality
phrase may amount to acknowledging less and less certainty which
participants may have wanted to avoid. In contrast, using an external
negative low probability phrase may simply indicate that new evidence
shows that the event is less likely than before. Future research
should disentangle the role of the directionality of probability
phrases in the preference for internal and external probability
phrases, for example by offering a choice between a crossing of
directionality and markers of the source (external low negative,
external low positive vs.  internal low negative, external low
positive). A corpus study of people’s preferences could also offer a
more ecologically valid picture of people’s preference.

\paragraph{Known and knowable outcomes are more often described with
internal probability phrases.} Our findings do not support that the
time location of an outcome (i.e., in the past or the future) is on its
own a predictor of the source of uncertainty that people choose to
convey. For example, when assessing their uncertainty about the
dangerousness of drugs, participants did not use a higher proportion of
internal probability phrases for drugs of the past than for drugs of
the future (Experiment 1). This hypothesis was derived from the common
assumption that past outcomes rely more on lack of knowledge – hence an
internal uncertainty – than future outcomes, which rely on both lack of
knowledge and world stochastic processes – hence a mixture of internal
and external uncertainty (Brun \& Teigen, 1990). However, the
relationship between temporality and the source of uncertainty might
not be as straightforward. We proposed that the knowability of an
outcome – the extent to which knowledge can reduce uncertainty – is a
better predictor of the source of uncertainty experienced than the
temporal location of the outcome. Results of Experiment 2 were
consistent with this hypothesis: participants consistently preferred
external probability phrases for past or present outcomes that are
unknowable (e.g., life on Mars) and preferred internal probability
phrases for past known and future predictable outcomes (e.g., the size
of the Eiffel Tower and sea rise in 2100). We could infer from these
findings that when making simple predictions, people have a preference
for internal probability phrases because there are more facts that are
known (e.g., the size of the Eiffel Tower) and future outcomes that are
predictable and will be known, over outcomes that are unknowable. 

\paragraph{Preference for markers of the source of uncertainty in
  conversations.} Many predictions are not done in a conversational
vacuum. Hence, we also investigated the role of previously voiced
opinions on participants’ preferences for internal and external
probability phrases. Our findings showed that participants mirrored
the source conveyed by their conversational partners, whether they
agreed or disagreed with them (Experiment 1). This finding opens a new
line of investigation, whereby the source of uncertainty of one person
can affect the source of uncertainty expressed by another, simply by
mirroring the choice of words and perhaps also by influencing the
recipient’s perceived source of uncertainty. Further research could
focus on the effect of internal and external probability phrases on
recipients’ perceived source of uncertainty. This mirroring in
conversation appears in line with the idea of coordination in dialogue
and conversational alignment (Garrod \& Anderson, 1987; Garrod \&
Pickering, 2004), characterized, for example, by lexical repetition
(Garrod \& Anderson, 1987; Garrod \& Pickering, 2004). In our
experiment, participants aligned their speech to their dialogue
partner by making the same lexical choice and reusing the same pronoun
subject.

By identifying factors that determine the preference for linguistic
markers of the source of uncertainty in language, we inform factors
that determine the type of uncertainty that people experience. Based on
the findings presented here, we can suggest that people experience more
internal uncertainty when experiencing higher levels of certainty, and
knowability of the outcome, whether they gain more certainty by
learning or over time. We have also shown that more incidental
contextual factors drive the preference for markers of the source of
uncertainty, such as the marker of the source used by a dialogue
partner. In this case, the marker of the source may have a difference
function: to increase the social coordination between dialogue
partners. 

Building on the finding that, out of a dialogue, the pronoun subjects of
probability phrases are used as markers of the source of uncertainty of
the speaker, which is itself derived from specific contexts, one could
expect that hearers of those markers would make specific inferences
about the speaker and the context. We have tested this hypothesis in
two experiments.

\renewcommand{\baselinestretch}{1.04} \large\normalsize

\subsection{Insight into what recipients infer from linguistic markers of the source
of uncertainty}

\paragraph{Inferences about the speaker.} Speakers uttering external
probability phrases were hypothesized to be perceived as more
knowledgeable (Løhre \& Teigen, 2016), but this was not found
consistently (Løhre \& Teigen; Experiment 1 vs.\ Experiment 3 and 4).
The present paper’s findings (Experiments 3 and 4) shed some light on
the reasons why results were inconsistent. A probability phrase with a
third person neuter pronoun subject was not a sufficient condition for
the speaker to appear as more knowledgeable. However, the pronoun
subject did determine the perceived knowledge of the speaker, in
interaction with the probability conveyed in the prediction and the
expertise of the speaker. For example, hearers inferred that novices
uttering external probability phrases were more knowledgeable than
novices uttering internal probability phrases, whereas they inferred
the opposite from expert speakers, who were considered as more
knowledgeable when they gave internal phrases. Our results did not
support that the use of internal or external probability phrases was a
cue of the speakers’ wishes (Experiment 3 and 4). This appears in
contrast with Løhre and Teigen’s findings, showing that, in the
context of football predictions, internal probability phrases led
recipients to believe that the speaker supported the team more than
external probability phrases did (Experiment 4). The designs of the
studies differ in a key point: we kept the probability conveyed by the
speaker as constant (e.g., \textit{quite certain}) and varied only the
pronoun subject of the sentence (e.g., \textit{I am} \textit{quite
  certain} vs.  \textit{It is quite certain}). In contrast, Løhre and
Teigen asked participants to complete an internal or external
probability phrase with the numerical probability that would be most
appropriate before they assessed the attitude of the speaker. The
probability associated with internal probability phrases was higher
(e.g., \textit{I am 57\% certain} …) than in the external condition
(e.g., \textit{It is 45\% certain}), hence the probability phrases
differed by more than the pronouns they featured. Speakers uttering an
internal probability phrase may have been perceived as more supportive
of the target team because they also conveyed a higher probability
that the team would win.

\paragraph{Inferences about the prediction.} In line with previous
findings, our data showed that recipients judged external probability
phrases as more informative than internal probability phrases. This
replicates previous findings of the effect of the markers when
associated with numerical probability phrases (Løhre \& Teigen, 2016).
In addition, consistent with Løhre and Teigen, we found that recipients
did not think that internal probability phrases were more likely to be
based on intuition than external probability phrases.

\paragraph{Inferences, implications for decision-making.} As noted by
Løhre and Teigen (2016), the internal-external probability distinction
does not have a place in normative decision-making models but should
definitely feature in descriptive models of decision-making, given
that the source of uncertainty reflects a psychological reality that
affects people’s judgments and decisions. The source of uncertainty
conveyed via the pronoun subject of the probability phrase did not
have a main effect on the decision, but it interacted with the
probability conveyed by the speaker and with his expertise to affect
willingness to bet.  Participants were more willing to use a low
external probability phrase than a low internal probability phrase in
betting but would rather use a high internal probability phrase than a
high external probability phrase (Experiments 3 and 4). Further,
participants were somewhat more willing to bet based on an internal
probability phrase voiced by an expert, but keener to bet based on an
external probability phrase voiced by a novice (Experiment 4).

We offer here insights into the properties of probability phrases, the
determinants of their selection and their effects on the judgments and
decisions of recipients. This could inform risk communication in
different key societal domains, where risk communication is seen as a
major challenge, such as in finance (Doupnik \& Richter, 2003, 2004;
Laswad \& Mak, 1999), climate change (Budescu, Broomell \& Por, 2009;
Budescu, Por, Broomell \& Smithson, 2014; Budescu, Por \& Broomell,
2012; Patt \& Schrag, 2003; Patt \& Suraje, 2005; Sterman, 2011),
medicine (Berry \& Hochhauser, 2006; Berry, Knapp \& Raynor, 2002;
Berry, Raynor \& Knapp, 2003), sentencing decisions (Dhami, 2008) or
military intelligence (Dhami, Mandel, Mellers \& Tetlock, 2015;
Hastie, 1993). The difficulty of communicating uncertainty has led some
regulatory bodies (e.g., the IPCC for climate change) to recommend the
use of a reduced list of probability phrases. However, these lists do
not feature the pronoun subject to be used and, hence, still leave room
for variability. The features of probability phrases can be seen as a
challenge but could also be seen as an asset that could be harnessed to
develop more effective risk communication guidelines. For example,
experts should use more internal probability phrases to appear more
convincing whereas novices may be more effective by using external
probability phrases. 

\subsection{Conclusion}

In four experiments on uncertainty communication, we focused on the
interpretation of whole probability phrases rather than isolated
probability words (e.g., \textit{I am certain} instead of
\textit{certain}) in which we manipulated the phrase subject (I am
uncertain vs.\ it is uncertain). The present research brings some
innovative findings about the factors that drive the preference for
internal and external probability phrases. Results showed that
participants exhibited consistent preference patterns, depending on
their subjective probability, the degree to which knowledge could
reduce uncertainty and, in dialogue, based on the source of uncertainty
conveyed by a dialogue partner. The present paper demonstrates that
pronoun subjects are (among other usages) used as linguistic markers of
the source of uncertainty of the speaker, and that they affect
recipients’ judgments and decision-making.

\renewcommand{\baselinestretch}{1.0} \large\normalsize

\section*{References}
\begin{hangparas}{1em}{1}

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%\vfill
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\end{hangparas}.

%\bigskip

\section*{Appendix: Questionnaire used in Study 2}

Below you will find a set of pairwise statements that express different
degrees of certainty or uncertainty. Your task is to compare the two
sentences in each pair and place a cross next to the sentence that
appears more natural and sounds like an actual occurring statement.
Even if they both seem natural, try to select the one that most likely
is a genuine quotation. 

\medskip\noindent
1 [known\_HighP]

(a) It is almost certain that UN was founded after the war 

(b) I am almost certain that UN was founded after the war 

\medskip\noindent
2 [Predictable\_HighP]

(a) It is quite certain that Spain will get to the 2012 European
Football Championship 

(b) I am quite certain that Spain will get to the 2012 European Football
Championship

\medskip\noindent
3 [Known\_LowP]

(a) It is uncertain whether Sweden won the last match against Denmark 

(b) I am uncertain about whether Sweden won the last match against
Denmark 

\medskip\noindent
4 [Predictable\_LowP]

(a) It is uncertain whether Sweden will win the next match against
Denmark 

(b) I am uncertain whether Sweden will win the next match against
Denmark 

\medskip\noindent
5 [Unknowable\_HighP]

(a) It is quite certain that there is life on other planets

(b) I am quite certain that there is life on other planets

\medskip\noindent
6 [Unknowable\_LowP]

(a) It is uncertain whether Robin Hood has actually lived

(b) I am uncertain about whether Robin Hood has actually lived

\medskip\noindent
7 [Known\_Low]

(a) It is uncertain whether Lithuania is south of Latvia

(b) I am uncertain about whether Lithuania is south of Latvia

\medskip\noindent
8 [Known\_High]

(a) It is certain that Toulouse is in France

(b) I am certain that Toulouse is in France

\medskip\noindent
9 [Predictable\_Low]

(a) It is not certain what I will do tomorrow

(b) I am not certain what I will do tomorrow 

\medskip\noindent
10[Predictable\_Low]

(a) It is not certain that Hans will accept the offer

(b) I am not certain that Hans will accept the offer

\subsection*{Part II}

\noindent
Which of these two sentences are more convincing?

(a) It is certain I will arrive in time

(b) I am certain I will arrive in time

\medskip\noindent
Which of these speakers will finish first?

A says: “It is not certain I will be finished on Monday”

B says: “I am not certain I will be finished on Monday” 

\end{document}
