






































Advances in Politics and Economics
ISSN 2576-1382 (Print) ISSN 2576-1390 (Online)

Vol. 5, No. 1, 2022
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73

Original Paper

Hidden Affections: Presumptions that Continue to Misshape 

The Measurement of Emotion
George E. Marcus1

1 Department of Political Science, Williams College, Williamstown, United States

Received: January 4, 2022     Accepted: January 21, 2022     Online Published: January 24, 2022 

doi:10.22158/ape.v5n1p73          URL: http://dx.doi.org/10.22158/ape.v5n1p73

Abstract

All empirical investigations rely on formative presumptions. Over the past 70 plus years, research on 

emotion has long been reliant on data collected using subjective responses and by experimental 

exposure to target stimuli, and increasingly with various brain scanning technologies. During this 

period neuroscience research greatly contributed to our understanding of how emotions are formed 

and what functions they perform in the realm of politics and social life more generally. I identify a 

number consequential presumptions, in some differing combinations, that have been the foundations 

for commonly used measures of emotion and measurement practices. These presumptions enable 

research that has generated a considerable empirical literature. But these presumptions have become 

increasing tenuous as insights produced by neuroscience has slowly been integrated into the 

measurement of emotion. The measurement of emotion has gradually adopted these new insights. The 

adjustments and benefits that derive are described in the final section.

Keywords

Emotion, operationalization, presumptions, preconscious awareness, conscious awareness

Hidden Affections: How Presumptions Shape The Measurement of Emotion

“In a very crucial sense there is no methodology without logos, without thinking about thinking. And if 

a firm distinction is drawn—as it should be—between methodology and technique, the latter is no 

substitute for the former. One may be a wonderful researcher and manipulator of data, and yet remain 

an unconscious thinker.”

Giovani Sartori (1970, p. 1033)

“People are not liable to be mistaken in their feelings, but they are frequently wrong in the names they 

give them, and in their reasoning about them.”

Edmund Burke (2009, p. 30)



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1. Introduction

Emotion, once it emerged from its prior disregard in the social sciences, has become an essential topic 

in the effort to secure a sound understanding of how people form judgments, especially political 

judgments (Brader & Marcus, 2013).

Scientific inquiries begin with selecting a methodology for generating data. The validity of substantive 

conclusions rest on the validity of the data used to reach those conclusions. As to measuring emotion 

there have been a number of important journal articles on emotion measurement in psychology and 

political science that have advanced our understanding of how to measure the emotions people 

experience. Among these are those by David Watson and colleagues (Watson et al., 1988; Watson, 

1988; Watson & Clark, 1991; Watson & Clark, 1997; Gray & Watson, 2007; Watson et al., 2017); 

Harmon-Jones and colleagues (Harmon-Jones et al., 2016); Albertson and Gadarian (Albertson & 

Gadarian, 2016); Searles and Mattes (Searles & Mattes, 2015); Marcus and colleagues (Marcus & 

MacKuen, 1995; Marcus et al., 2006; Marcus et al., 2017); Rhodes-Purdy and colleagues (Rhodes-

Purdy et al., 2021); Karl Scherer (Scherer, 2005); and, Junge and colleagues (Junge & Reisenzein, 

2013; Junge & Reisenzein, 2016). While advancing the measurement of emotion, there remain aspects 

of emotion measurement not yet fully explored. In this review I seek to identify some remaining 

problems with some extant measures and practices.

Giovani Sartori’s directive suggests that some scientific understandings can be so comfortably settled 

that their influence is both powerful and hidden. And, as such, they may block reaching better 

understandings (Danner et al., 2016). This can be the case even as many contemporary emotion 

theorists make no mention of these presumptions.

My intentions are to make visible the presumptions that underly four commonly used measurements of 

emotion and measurement practices. Each of these have been selected because the measurements and 

validation practices preclude testing the validity of their presumptions:

1) Feeling thermometer and other measures reliant on a valence formulation of emotion. 

2) Embedding a “think instruction” before asking people to rate a target stimulus using a list of emotion 

words.

3) Continued use of the PANAS schedule on the preemption its list of twenty affect words is a 

comprehensive sample of emotions.

4) Use of target stimuli and other means of affect induction without any or with insufficient 

manipulation checks.

One theme this review will be to show that developments in the neuroscience of perception and of 

emotion challenge the validity of these practices. Another theme is to demonstrate how the 

development of new measures and modes of analysis of emotion freed from these presumptions has 

generated new and consequential understandings of emotion and then new insights on the ways 

emotions impact on action and judgment.

Table 1 list four presumptions that have continued to shape empirical investigation of emotions. 



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Table 1. Presumptions Influential in Emotion Measurement

1. Depicting Emotion as Valence

2. Thinking generates more accurate emotion assessments

3. Focusing on ‘Peak’ Emotion

4. Understanding Emotion as Monochromatic

2. Presumptions

2.1 Affect as Valence

A core presumption has long been that humans respond to reward and punishment (Skinner, 1969; 

Wilson et al., 1989a; O’Dougherty et al., 2001). This focus on reward-approach and punishment-

avoidance has long been a central feature of models of learning and psychology more generally 

(Patterson et al., 1987; Tesser & Martin, 1996). Thus, identifying any external individual, group, or 

other object as positive or negative serves to address this fundamental concern. As Lodge and Taber 

(2005, p. 456) put it: 

“All political leaders, groups, issues, symbols, and ideas thought about and evaluated in the past 

become affectively charged—positively or negatively—and this affect is linked directly to the concept 

in long-term memory. This evaluative tally, moreover, comes automatically and inescapably to mind 

upon presentation of the associated object, thereby signaling its affective coloration...”

Emotion, here, has been tasked with identifying the reward-punishment status of any object or activity 

under consideration. Valence remains a core accepted scientific concept as for example in 

investigations of “campaign sentiment” (Geer, 2006; Haselmayer, 2021) as well as the broad class of 

theories, such as utility theory and prospect theory, that attend to gain or loss; punishment or reward 

(Skinner, 1969; Kahneman & Tversky, 1979).

2.2 Think Instructions Elicit more Accurate Responses

The presumption is that if one directs people to think about the matter that will yield, on balance, more 

accurate assessments than leaving people to muddle through without such a direction. The well-

established Elaboration Likelihood model gives weight to this presumption. Hence, it can be safely 

anticipated that invoking focused attention to a judgment task will enhance the motivation to secure a 

more accurate understanding (Petty & Cacioppo, 1986, p. 127).

2.3 The Peak Emotion Presumption

The peak emotion presumption holds that peak levels of any discrete emotion, be it, joy, fear, anger, or 

any other discrete, or basic, emotion, reveals what is necessary to know about that emotion. Moreover, 

peak emotions are presumed to take over, that is, exclude other emotions from playing a concurrent 

role of consequence with the exception of the condition of ambivalence, discussed below. Hence, it is 

best to study a given emotion in circumstances were it can be expected that emotion is most likely to be 



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prominent. For example, in the realm of negative emotions it is the attention grabbing events such as 

terror attacks, financial crises, pandemics, or high stake political confrontations, that best reveal the 

influence of negative emotions (Finseraas & Listhaug, 2013). As a result there has been less interest in 

low levels of discrete emotions because discrete emotions in the mundane normal activities of life are 

presumed to have less consequence on judgment. And, it encompasses the possibility of a state of mind 

that is non-emotional (Gennaro & Ash, 2021). 

2.4 The Monochromatic Presumption

Attitude theory and cognitive appraisal theories long presumed that people, at any given moment, 

normally experience one singular dominant emotion. This is the monochromatic presumption. If we 

describe ourselves as feeling happy, that is because we are happy. If we describe ourselves as fearful, 

that is because we are fearful (Roseman, 1984). 

The notion of ambivalence, a condition thought to arise when people experience simultaneous 

conflicting feelings about someone or something, asserts the possibility that people may experience 

multiple concurrent emotions (Craig & Martinez, 2005). However, the study of ambivalence envisions 

a very limited possibility of multiple concurrent emotions. Two conceptual limitations have constrained 

this research area. First, the general view is that instances of ambivalence are relatively rare. Second, 

the notion of ambivalence expressly limits the consideration of multiple emotions to two, the “bi” in 

ambivalence, one of which is positive and the other being negative, the “valence” in ambivalence 

(Lavine et al., 2012). An expanded consideration of multiple concurrent emotions and their distinct 

consequences foretells the future of research on emotion. One of the most enduring and detrimental 

impact of this presumption can be viewed in emotion induction experiments.

I next turn to the data generation practices that to some extent are dependent on one or more of these 

presumptions.

3. Measuring Emotion

3.1 Measuring Emotion as Valence

Feeling thermometers seek to answer to the question: Is this something we like and are inclined to 

approach, or something we dislike and are inclined to avoid (Cosmides & Tooby, 2000)? Feeling 

thermometers conceive emotion as a single valence factor. The American National Election Studies 

(ANES) operationalization is shown in Table 2. It remains a popular and frequently used measure of 

emotional attachment (Warner et al., 2021).

Table 2. The Feeling Thermometer

“I’d like to get your feelings toward some of our political leaders and other people who are in the news 

these days. I'll read the name of a person and I'd like you to rate that person using something we call 

the feeling thermometer. Ratings between 50 degrees and 100 degrees mean that you feel favorable and 



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warm toward the person. Ratings between 0 degrees and 50 degrees mean that you don’t feel favorable 

toward the person and that you don't care too much for that person. You would rate the person at the 50 

degree mark if you don't feel particularly warm or cold toward the person. If we come to a person 

whose name you don’t recognize, you don't need to rate that person. Just tell me and we’ll move on to 

the next one.”

Source: (Overseers, 2021, p. 83).

The measurement scheme precludes challenges to its validity. Willingness to rate leaders, groups, 

events, or policies does not thereby establish its scientific validity.

Challenges: Three challenges to the validity of feeling thermometers have arisen over the past half-

century.

First, the identification of feelings as measuring emotional response, i.e., as a mechanism of memory, 

has been challenged by research holding that affective appraisals arise well before consciousness 

(Lodge & Taber, 2005).

Second, also more fully discussed below, when multiple measures of emotion are gathered, initial 

analyses found two dimensions of response, commonly labeled positive emotion and negative emotion. 

That is they find they do not use the multiple measures to produce single valence measure (Abelson et 

al., 1982; Watson & Tellegen, 1985).

Finally, thirdly, the feeling thermometer measure also rests on the presumption that negative emotion is 

a coherent scientific property (Hibbing et al., 2014; Mattes & Redlawsk, 2014). Yet for over twenty 

years the identification of two “negative” emotions, fear and anger, each with different neural 

underpinnings, each with different consequential antecedents, and each with differing downstream 

impacts on information processing generally, and judgment specifically, have been readily available in 

political science and psychology journals (MacKuen et al., 2010; Marcus et al., 2019; Lerner & 

Keltner, 2000; Lerner et al., 2003; Skitka et al., 2006; Suhay & Erisen, 2018). Indeed, this recent 

recognition of bifurcation within the domain of negative emotions had arisen many years prior (Arnold, 

1950; Ax, 1953).

There has been one effort to reassert the validity of valence. James Russell accepted that data gathered 

by multiple emotion word check lists does generate a dense two-dimensional array. He shows how, by 

rotating the dimensions by 45°, the two dimensions that then be plausibly be labeled valence and 

arousal (Russell et al., 1989). Russell’s alternative leaves us with two dimensions, as before, just 

relabeled in a fashion that serves to preserve a nominal valence dimension. Related to this proposal is 

the idea of “core affect” (Bakker et al., 2021). Central to this construction is the notion of good-

positive-liking versus bad-negative disliking, the essence of the valence concept. But, as Karl Popper 

argued (Popper, 2000, p. 333):



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“Every ‘good’ scientific theory is a prohibition: it forbids certain things to happen. The more a theory 

forbids, the better it is. A theory which is not refutable by any conceivable event is non-scientific. 

Irrefutability is not a virtue of a theory (as people often think) but a vice.” 

While feeling thermometers are not themselves a theory, they are dependent on the validity of the 

theoretical claim that emotion is validly treated as a singular dimension that ranges from strongly like 

to strongly dislike.

3.2 Improving Accuracy when Measuring Emotion

As a social species, humans have a robust capacity to join with others into a group, whether small, as in 

a family, or very large, such as citizens of a nation. Hence, exploring group identification has been a 

central focus of research in the social sciences (Huddy, 2001; Huddy, 2018). The standard party 

identification measure in the United States, then and now, instructs study participants to think who they 

align with rather how they feel about the parties. The instruction is “Generally speaking, do you usually 

think of yourself as [a Democrat, a Republican, an independent, or what?” (Note 1) Here, questions 

beginning by instructing people to think about their feelings of attachment is presumed to produce more 

accurate and valid responses.

A recent example of this belief that accuracy in the measurement of emotion is enhanced by the “think” 

instruction is offered by Rhodes-Purdy and colleagues (Rhodes-Purdy et al., 2021). The rationale for 

using this instruction is worth quoting (Rhodes-Purdy et al., 2021, p. 7): 

Our approach should lead to more accurate reports of discrete emotional responses in several ways. … 

Forcing individuals to think in greater depth about a topic causes them to produce responses that are 

more complex … More effortful processing of information, as required by this two-step task, can lead 

to better decision-making … that is slower and more logical … which may give us higher quality, and 

more accurate, self-reports of emotion.” 

Challenges: There is considerable evidence from a number of studies showing that the think 

instruction condition does indeed change how people respond when compared to either no instruction 

or to feel instruction conditions. But rather than improving accuracy, these studies show that the think 

instruction generates biased estimates (Wilson et al., 1989b; Theiss-Morse et al., 1993). Specifically, 

with respect to measuring partisan attachment, measuring emotional identification to one’s party that 

use the "think” instruction yield distributions that overstate the percentage of Democrats and understate 

the percentage of Republicans in any given sample (Burden & Klofstad, 2005; Neely, 2007).

3.3 Using Emotion Words to Measure Emotion

In the 70s and 80s the then popular “cognitive appraisal theories” of emotion offered a number of more 

complex taxonomic arrays than the simple one dimensional valence conception (Tomkins, 1984; 

Ortony et al., 1989; Roseman, 1984). The fundamental presumption, applicable to all variants of the 

cognitive appraisal approach, was that general considerations are sequentially applied which then 

determine the "basic” or "discrete” emotions that is made manifest in consciousness (Smith et al., 

1993). Basic emotions are commonly understood as a set of affective states that form a taxonomy of 



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monochromatic states. Various taxonomies of these "discrete” states were proposed (Tomkins, 1984; 

Ekman, 1992; Ortony et al., 1989; Roseman, 1991; Lazarus & Lazarus, 1994). 

The Izard Differential Emotion Scale (Izard, 1977) was one of the earliest efforts to operationalize the 

discrete approach to emotion. Study participants are presented a list of discrete emotions and then 

asked which of these they have ever felt, either recently or over a specified prior period. There is no 

external target, i.e., the interest was in the subjective state of the individual, not feelings about 

something out there. In political science research on emotion has generally not been directed at the 

introspective, rather emotions have been examined as informative reactions to the state of the world 

(Conover & Feldman, 1986). In psychology, Norbert Schwarz (1990) also argued for this shift in focus, 

to emotions as informative about some aspect of the external world.

In the 1980 Election Study, of what is now the American National Election Studies (ANES), 

introduced a version of the Izard Differential Emotion scale. The exact wording of this 

operationalization reveals the embedded presumptions. Below is the instruction for the Candidate 

Feeling Scale:

“Now we would like to know something about the feelings you have toward the candidates for 

President. I am going to name a candidate, and I want you to tell me whether something about that 

person, or something he has done, has made you have certain feelings like anger or pride.” 

Thereafter, the major presidential candidates were named and for each candidate seven emotion words 

randomly presented: angry, hopeful, afraid, proud, disgusted, sympathetic, and uneasy. (Note 2)

Challenges: It quickly became apparent that individuals, when given a check list of supposed discrete 

emotions did not treat them as mutually exclusive alternatives. Rather, they treated them as equally 

useful markers for their feelings (Abelson et al., 1982; Tellegen, 1985; Watson & Tellegen, 1985). 

Moreover, when such lists were offered analyses of these responses generated a “circumflex” (i.e., a 

dense circle wherein all emotion words can be plotted) that is a two-dimensional space. (Note 3)

This development enabled a new line of inquiry into emotion. Rather than the longstanding interest in 

which emotion becomes active, emotion word check lists enable emotion to be treated as appraisal 

rather than as response. And, further, directs attention to how changing levels of any given emotion, 

across the full range of that emotion, impact on downstream action and thought.

Using lists of emotion words as multiple indicatorsoflatent scientific concepts of emotion treats 

emotion words as a way of identifying their meaning rather than by reference to a dictionary (Sullivan 

& Feldman, 1979). The immediate challenge was, and remains, how to select emotion words from the 

hundreds available in the English lexicon (Storm & Storm, 1987; Clore & Ortony, 1988; McEachrane, 

2009). David Watson and colleagues (Watson et al., 1988), after examining many emotion words, 

selected the following twenty emotion words as reliable indicators covering the diverse domain of 

emotion: interested, distressed, excited, upset, strong, guilty, scared, hostile, enthusiastic, proud, 

irritable, alert, ashamed, inspired, nervous, determined, attentive, jittery, active, and afraid. These 

words formed the Positive and Negative Affect Schedule (PANAS).



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David Watson, not long after publishing the PANAS scale, recognized the relative paucity of negative 

emotion words suitable to identifying anger as an emotion distinct from fear. He, and his colleague Lee 

Anna Clark, developed a far fuller array of emotion words in the PANAS-X schedule to correct this 

lacunae (Watson & Clark, 1994). However, that important elaboration has not gained sufficient 

attention as many researchers continue to use the original PANAS schedule (Heubeck & Wilkinson, 

2019). The PANAS-X schedule has been largely ignored thereby delaying exploration of the distinction 

between fear and anger (Marcus et al., 1995; Lerner & Keltner, 2000).

Much depends on which of the hundreds of emotion words best define a distinct emotion. Consider the 

word choices English speakers have available to describe their feelings when violated in some fashion 

by someone or some group. They might choose any of these: rage, angry, wrathful, ire, annoyed, 

hassled, vexed, bothered, upset, insulted, peeved, pestered, offended, menaced, troubled, hateful, 

exasperated, irritated, ruffled, affronted. There are more than just these twenty readily available (e.g., 

cross, disgusted, disdain, bitter, incensed, infuriated, resentful, and, scorn). Why so many and, more 

importantly, how are they different?

One type of difference is emotion words is that some are equally applicable to a single appraisal, either 

as synonyms for that one appraisal, or as names of different levels of that appraisal, i.e., identifying 

whether the underlying feeling is more robust or more mild. Moreover, even if some of the many words 

are synonyms one might choose one rather than another because of the social context, for example, 

being among friends, or alone, or among strangers.

Another way emotion words might differ in meaning is by identifying differences of kind. We say we 

are “angry” when we feel we have been wronged, i.e., have a grievance. On the other hand, we might 

say we are “happy” when we feel some success. Each emotion word identifies a different distinct 

appraisal, how much grievance for the first, and how much success for the second (Calder et al., 2001). 

Inattention as to whether emotion words differ in their use as identifying the level of a given property 

or by identifying difference in kind is common in the social sciences (Dunn & Schweitzer, 2005). That 

inattention has led to considerable taxonomic confusion as to which emotion words identify differences 

in degree (i.e., applicable to stronger and weaker levels of a given emotion), and which are differences 

in kind.

Some hold that disgust and anger are different emotions, that is different in kind (Clifford & Jerit, 

2018; Molho et al., 2017; Giner-Sorolla & Russell, 2019). Others argue for a distinction between fear 

and anxiety (Cheung-Blunden et al., 2018) or for contempt as distinct from anger and from disgust 

(Roseman et al., 2020). Others hold that hope and enthusiasm are distinct emotions (Just et al., 2007) 

and yet others that there are ten different positive emotions (Van Zomeren, 2021). Some argue for more 

distinctions, while others hold for fewer. For example, some hold that disgust, contempt, fear, anger 

just members of the negative class of emotion (Hibbing et al., 2014). That is, emotion as valence is 

valid and a valence measure can be used to capture what emotions are and what they do (König et al., 



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2021). Testing whether these named emotions are different from each by degree or kind is, too often, 

largely absent. This leaves the category of “basic” emotion largely ill-defined.

There are multiple criteria that can be used to test claims of that specific emotion words identify 

difference in kind while others identify as synonyms. Among these are:

1) Do people use a some emotion words as synonyms for a single emotion and do they differentiate that 

emotion from others (Marcus et al., 2017)? 

2) Are different antecedents showing differentiating effects on the distinct emotions (Gerbella et al., 

2019)?

3) Have distinguishing consequences for judgment and behavior that have been empirically 

demonstrated, for example, as to fear versus anger (MacKuen et al., 2010)?

4) Have distinct neural structures and processesidentified distinct neural affective appraisals (Calder et 

al., 2001; Paulus et al., 2010; Maratos et al., 2012; Phillips et al., 2004)?

Too often none of the above are used to justify treating emotion words as being valid markers of a 

given emotion. (Note 4)

3.4 The Validity of the Experimental Practices and Emotions Research

Experiments are a popular method for exploring emotion. Experiments on emotion commonly rest on 

the presumption that it is possible to induce the discrete emotion of interest. Experiments begin by 

randomly assigned some participants to receive the target emotion induction. This group can then be 

compared to others who have not been given that induction. Richer research designs can and do include 

differing inductions so that some participants would be induced to experience emotion A while others 

emotion B, and so on. The induction might make use of one or more faces from the set of Ekman faces 

(2005) or of the pictures that make up the Lang Universal Affect Inventory (1988). Some researchers 

have generated specific materials to induce the emotions of interest (Searles & Mattes, 2015). Yet, 

another approach is to ask participants to recall and describe a specified discrete feeling state thereby 

presumably making the emotion of interest consciously present (Valentino et al., 2011). Additionally 

sound, generally, and voice, specifically, have been used to activate a specific emotion (Bradley & 

Lang, 2000; Brader, 2006; Dietrich et al., 2019; Kim et al., 2016). The benefit of using stimulus of 

some proven validity is of obvious value but that value, as I shall argue below, has limitations.

Challenges: An important means of validating the claim that the treatment has the intended effect is 

the use of manipulation checks (Fiedler et al., 2021). Emotion induction, as practiced (Fakhrhosseini & 

Jeon, 2017), is commonly reliant on the presumption that the impact of the induction on the target 

emotional state is monochromatic. This presumption has the effect of obscuring the need exclude the 

possibility that other emotions might also be impacted by exposure to the treatment. Research has 

shown there is considerable evidence that multiple concurrent affective appraisals is the norm, not the 

exception (Whalen et al., 2001; Maratos, 2011; Maratos et al., 2012; Marcus et al., 2017).

As Mutz and Permante (2015) have persuasively argued, it is essential to include manipulation checks 

to validate the claim that the affective state of interest has been successfully manipulated by the 



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treatment. However, it is equally vital to use manipulation checks to assess whether other concurrent 

affective states have not been manipulated or, if altered, have data on these concurrent affective 

changes so that they can be controlled by multivariate statistical analysis.

Producing better measures and analysis practices for research on emotion requires is a new theoretical 

foundation. I turn to that next.

4. A Neuroscience Informed Theory of Perception

Various appraisal theories hold the presumption that appraisal is prior and emotion is the consequential 

result, hence emotion is commonly labeled: emotional response. For example, the emotion regulation 

approach from the outset presents emotion as a derivative response (Katz et al., 1974; Gross, 1998; 

Tamir et al., 2020). The recognition that there are consequential information processes that act before 

conscious awareness has long been shown to be ubiquitous (Libet et al., 1979; Zajonc, 1980; Freeman 

& Johnson, 2016). But this recognition is often couched in spatial terms, e.g., subliminal versus liminal 

(Winkielman & Berridge, 2004) or the lower and higher reaches of the brain (Kosslyn & Miller, 2013). 

Finding the right language to describe how affective processes and consciousness are related requires a 

new understanding of perception. This new understanding is briefly described below.

In the late 60s and early 70s neuroscience research revealed some important insights that profoundly 

undermined the psychology of perception that had hitherto provided the foundation for ongoing 

programs of research into emotions. The research of neuroscientist Benjamin Libet (1979) revealed that 

though conscious awareness come with a sense of immediacy this sense is largely an illusion, see also 

(Nørretranders, 1998). His research revealed that during the 500 milli-second period that lies between 

the arrival of sensory signals to the human brain and the availability of consciousness, massive parallel 

preconscious processes are creating actionable understandings that shape and control much of what we 

do (Castiello et al., 1991). The brain generates actionable awareness considerably earlier than does the 

conscious mind.

Preconscious processing enables deft and swift control of habituated actions well before and well 

beyond what conscious control can sustain (Freeman & Johnson, 2016; Hoffman, 2019). Three features 

of preconscious processing are of particular importance. 

First, preconscious multiple concurrent, but distinct appraisals, have greater capacity than the more 

limited serial subjective experience of consciousness (Grossberg, 2000). For example, our tongues have 

difference kinds of taste cells each tuned to a different facet of taste: sweet, sour, salty, bitter, and 

umami. These, together with yet other types of cells in the mouth that add assessments of pain, 

temperature, and texture, generate in consciousness the coherent taste and feel of something we’ve 

ingested. 

The brain does not wait for the mind’s late awareness to take action. Swift identification and initiating 

the disgorging response to what is foul is vital to limit the danger of ingesting something poisonous and 

dangerous to life (Rozin & Fallon, 1987). Waiting for the necessary passage of time for conscious 



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recognition after ingesting something possibly poisonous is an unlikely route for securing 

environmental fitness (Herzog et al., 2016). 

Second, in addition to being slow, consciousness does not have introspective access to the full sensory 

information the brain receives from the senses. Preconscious neural processes are far more capable of 

handling the vast volume of sensory and somatosensory inputs then is conscious awareness. 

Consciousness has available a late and far simplified representation of that information.

Third, affective preconscious appraisals, because of their early and greater capabilities, are essential to 

successful thought and action (Bechara et al., 1995). In addition to having earlier and richer capacity to 

assess sensory and somatosensory input, preconscious processes also have access to essential neural 

systems that conscious awareness lacks. Among these are the vestibular system, procedural memory, 

and the motor cortex, to name but three of the most important. This changes how we should think about 

emotion, rather than understanding “Emotions [as having] the power to change how people perceive 

the (political) world” (Widmann, 2021, p. 163), we should understand that emotions are preconscious 

perceptions of the world.

Perception is best understood as beginning with multiple concurrent appraisals (Luo et al., 2007). The 

illusion of consciousness as giving humans instantaneous access to all we perceive is so powerful that 

social scientists, as do we all, use spatial terms—such as liminal versus subliminal—in discussing 

mental dynamics (Kouider & Dehaene, 2007; Baumeister et al., 2007). Figure 1 presents a schematic 

map reimagining perception and its relationship to emotion.



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Figure 1. Preconscious Emotion and Conscious Awareness

Figure 1 displays a fundamental shift from where emotion and thinking are located to when they each 

take place and which variant of reasoning is thereby made manifest and by which actions deftly 

executed. The temporal border between the preconscious realm and that of conscious awareness is 

generally placed at 500 milliseconds after sensory signals arrive in the brain (Matsuhashi & Hallett, 

2008). Moreover, this new understanding redefines emotion as cognitive in that these affective 

appraisals are fundamentally information processing. This reformulation focuses on the continuously 

shifting levels of multiple affective appraisals and the dynamic consequences that flow there from 

before consciousness is available (Sander et al., 2005).

Some appraisal scholars have begun to accommodate to the newer understanding of perception 

(Scherer & Moors, 2019). Appraisal theorists continue important comprehensive programs of research 

(Scherer & Moors, 2019; Barrett & Satpute, 2019) but, a not inconsiderable portion of contemporary 

published research has become narrowly focused on individual affective states or to some seemingly ad 

hoc selection of emotions intermixing those that differ in degree, for example, happy and sad, with 

emotions that differ in kind, such as fear and anger (Mills & D’Mello, 2014).

4.1 Measuring Emotion Driven by Neuroscience Insights

We can map the changing conceptions of emotion over time. As shown in Figure 2, below, the 

conception of emotion has shifted from a one-dimensional formulation, valence, to a two-dimensional 



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formulation, two dimensions that depict a dense ‘circumplex’, to, more recently, a dense ellipsoid 

volume. The ellipsoid is a shaped generated by using three axes to represent three ongoing active 

appraisals scanning for three essential aspects of securing and support individual and collective agency. 

In the case of the two-dimensional circumplex the axes are conventionally treated as orthogonal. In the 

case of the ellipsoid that is not the case. Studies exploring threat, and using validated measures of fear, 

anger, and enthusiasm generally find the two threat related appraisals, fear and anger, are highly 

correlated (Marcus et al., 2017). Hence these two axes are positioned at an acute angle, reflecting their 

joint relevance in identifying the two different facets of threat. On the other hand, the axis depicting the 

ongoing appraisal of reward seeking habituated behavior is located somewhat oblique to the other two. 

(Note 5) Not depicted in Figure 2 is the shift in understanding from emotion as a result of prior 

appraisal to emotion as the neural mechanism of appraisal.



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Figure 2. Changes in Emotion Conception: Valence, Circumflex, and Ellipsoid



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One new insight that flows from unpacking negativity is that threat can now be understood not one 

property, but two. Threat is multi-faceted. Fear identifies one facet of threat: the degree of novelty 

evident in the moment. Anger identifies another facet of threat: the presence of one or more violation of 

norms that dictate the proper behavior for ourselves, our family and friends, and strangers (Haidt, 

2001). While we have long thought that it is sufficient to describe threats as being one thing, varying 

from weak and inconsequential to robust and deadly, our brains had long been using preconscious 

emotional appraisals to tell us that such abstractions were obscuring strategically consequential 

differences between threat as novelty and threat as norm violation (Marcus et al., 1995). More broadly, 

reliance on valence-based measures of emotion will continue to mask the attention the human brain 

gives to more nuanced and focused appraisals.

The long-standing focus on fear as the marker of threat (Hobbes, 1968; Jost & Napier, 2012) now 

becomes more complex as fear is but one vital appraisal used to identify threat. Research prompted by 

the concurrent presence of the anger appraisal has not only identified anger’s prominent role in 

identifying threat but reallocates many of the downstream consequences from fear to anger 

(Vasilopoulou & Wagner, 2017; Marcus et al., 2019). Pursuing that more complex understanding 

mandate methods of measuring emotion that can capture the independent dynamic shifting of fear and 

of anger in threat conditions. 

Finally, if changing levels of these appraisals initiate changes in later, downstream processes such as 

openness to persuasion, or social bonding, and the like, then all levels of these appraisals are 

consequential (Marcus, 2021). “Peak” levels are important, but then so too are all the levels of any 

specific appraisal. If fear is low, signaling a familiar environment, then swift reliance on the ‘tried and 

true’ is deft mode of judgment and action (Bargh & Chartrand, 1999). Both high and low levels of 

novelty are consequential. Similarly, if very low levels of anger signal the absence of norm violations, 

then people are better able to exercise their individual agency, a consequence of some contemporary 

relevance (Webster, 2018; Marcus, 2019).

5. Discussion

A principal purpose of this inquiry is to explore how often unattended presumptions have directed the 

operationalization of emotion. The presumptions considered here identify the attributes thought to 

define emotion. The earlier approaches have a very long history and so their advantages and 

disadvantages can be more readily observed and assessed than the more recent. Older missteps are 

more easily identified than current practices. We can expect that as we learn more, the current practices 

and measures thought to be valid will be improved or replaced.

The understanding of emotion as a holistic, subjective state, has made way for a new more complex 

dynamic understanding of emotion as multiple ongoing appraisals. And, these appraisals, at all levels 

of each appraisal, have consequence (Neuman et al., 2018). Hopefully further work on measuring 

emotion will enable both old ideas and new to be continuously re-evaluated, further enriching our 



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understandings of our affections in all their sundry influences. This is not a final reckoning, only the 

most recent. Measurement of concepts is an essential feature of empirical research. But measures serve 

best when their foundational presumptions are made visible so that their validity can be tested.

Acknowledgement

Professor Mihai Stoicu, Williams College, helped with the generation of Figure 2. Colleagues Jon 

Krosnick, Milton Lodge, Matthew Rhodes-Purdy, Gijs Schumacher, Kathleen Searles, John Sullivan, 

Steve Utych, and, David Watson, each offered very helpful comments on earlier versions of this paper. 

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Notes

Note 1. Follow up questions further refine identifiers as strong or not so strong, and if independent 

whether they lean to one or the other major party.

Note 2. The criteria by which some emotion words are taken to be naming basic emotions and which 

are names of ‘non-basic’ emotion remains largely unresolved (Celeghin et al., 2017; Ortony, 2021; 

Caruana, 2017).

Note 3.  The instruction to participants also included the direction has made you, i.e., past tense. 

However, subsequent research demonstrated that people respond as if the instruction is here and now 

(Watson, 1988).

Note 4. Psychophysiological measures have long been of interest as a promising means by which one 

could obtain valid measures of discrete emotions but over the past three decades little progress has been 

made in that venture (Cacioppo et al., 2000; Bakker et al., 2020). There is one exception to that 

assessment, FacialEMG (Cacioppo et al., 1986; Van Boxtel, 2010).

Note 5. These are approximations. As more data becomes available, from more studies, it is likely that 

we will find these axes are dynamically related.


