Prediction‐based processes appear to play an important role in language. Few studies, however, have sought to test the relationship within individuals between prediction learning and natural language processing. This paper builds upon existing statistical learning work using a novel paradigm for studying the on‐line learning of predictive dependencies. Within this paradigm, a new “prediction task” is introduced that provides a sensitive index of individual differences for developing probabilistic sequential expectations. Across three interrelated experiments, the prediction task and results (...) thereof are used to bridge knowledge of the empirical relation between statistical learning and language within the context of nonadjacency processing. We first chart the trajectory for learning nonadjacencies, documenting individual differences in prediction learning. Subsequent simple recurrent network simulations then closely capture human performance patterns in the new paradigm. Finally, individual differences in prediction performances are shown to strongly correlate with participants’ sentence processing of complex, long‐distance dependencies in natural language. (shrink)

What individuates the speech act of prediction? The standard view is that prediction is individuated by the fact that it is the unique speech act that requires future-directed content. We argue against this view and two successor views. We then lay out several other potential strategies for individuating prediction, including the sort of view we favor. We suggest that prediction is individuated normatively and has a special connection to the epistemic standards of expectation. In the process, we advocate some constraints (...) that we think a good theory of prediction should respect. (shrink)

Predictive processing has begun to offer new insights into the nature of conscious experience—but the link is not straightforward. A wide variety of systems may be described as predictive machines, raising the question: what differentiates those for which it makes sense to talk about conscious experience? One possible answer lies in the involvement of a higher-order form of prediction error, termed expected free energy. In this paper we explore under what conditions the minimization of this new quantity might (...) underpin conscious experience. Our suggestion is that the minimisation of Expected Free Energy is not in itself sufficient for the occurrence of conscious experience. Instead, it is relevant only insofar as it helps deliver what Ward et al. ( 2011 ) have previously described as a _sense of our own poise over an action space_. Perceptual experience, we will argue, is nothing other than the process that puts current actions in contact with goals and intentions, enabling some creatures to know the space of options that their current situation makes available. This proposal fits with recent work suggesting a deep link between conscious contents and contents computed at an ‘intermediate’ level of processing, apt for controlling action. (shrink)

This paper represents an attempt to better understand the educational expectations of Japanese university students. Eighty students were asked to indicate whether or not they felt there was some relationship between 24 English words. The results were then added and entered into a table where the number at each intersection of words represented the total number of students that felt there relationship between those two words. This table was then analyzed using Multidimensional Scaling to produce a two dimension plot (...) representing the relationship between these 24 words. Since the distance between the words the plot represents the level of similarity, a study of the result gives some insight into the educational expectations of these students. A description of the data collection and analysis, as well as, one possible interpretation of the results is included. (shrink)

Life history theory suggests that in risky and uncertain environments the optimal reproductive strategy is to reproduce early in order to maximize the probability of leaving any descendants at all. The fact that early menarche facilitates early reproduction provides an adaptationist rationale for our first two hypotheses: that women who experience more risky and uncertain environments early in life would have (1) earlier menarche and (2) earlier first births than women who experience less stress at an early age. Attachment theory (...) and research provide the rationale for our second two hypotheses: that the subjective early experience of risky and uncertain environments (insecurity) is (3) part of an evolved mechanism for entraining alternative reproductive strategies contingent on environmental risk and uncertainty and (4) reflected in expected lifespan. Evidence from our pilot study of 100 women attending antenatal clinics at a large metropolitan hospital is consistent with all four hypotheses: Women reporting more troubled family relations early in life had earlier menarche, earlier first birth, were more likely to identify with insecure adult attachment styles, and expected shorter lifespans. Multivariate analyses show that early stress directly affected age at menarche and first birth, affected adult attachment in interaction with expected lifespan, but had no effect on expected lifespan, where its original effect was taken over by interactions between age at menarche and adult attachment as well as age at first birth and adult attachment. We discuss our results in terms of the need to combine evolutionary and developmental perspectives and the relation between early stress in general and father absence in particular. (shrink)

Along with the rapid application of new information technologies, the data-driven era is coming, and online consumption platforms are booming. However, massive user data have not been fully developed for design value, and the application of data-driven methods of requirement engineering needs to be further expanded. This study proposes a data-driven expectation prediction framework based on social exchange theory, which analyzes user expectations in the consumption process, and predicts improvement plans to assist designers make better design improvement. According to (...) the classification and concept definition of social exchange resources, consumption exchange elements were divided into seven categories: money, commodity, services, information, value, emotion, and status, and based on these categories, two data-driven methods, namely, word frequency statistics and scale surveys, were combined to analyze user-generated data. Then, a mathematical expectation formula was used to expand user expectation prediction. Moreover, by calculating mathematical expectation, explicit and implicit expectations are distinguished to derive a reliable design improvement plan. To validate its feasibility and advantages, an illustrative example of CoCo Fresh Tea & Juice service system improvement design is further adopted. As an exploratory study, it is hoped that this study provides useful insights into the data mining process of consumption comment. (shrink)

Many philosophers think that a necessary condition on moral blameworthiness is that the wrongdoer can reasonably be expected to avoid the action for which she is blamed. Those who think so assume as a matter of course that the expectations at issue here are normative expectations that contrast with the non-normative or predictive expectations we form concerning the probable conduct of others, and they believe, or at least assume, that there is a clear-cut distinction between the (...) two. In this paper I put this widespread assumption under scrutiny and argue that it’s mistaken: although predictive and normative expectations are indeed distinct, there is no sharp separation between them. On the contrary, predictive expectations can have a substantial bearing on normative expectations in two related ways: they can recalibrate what is reasonable to expect of agents when responsibility attributions are at stake and they can help to uncover previously undetected excusing conditions. I illustrate my claims with the famous bystander effect from social psychology and show that it yields predictive expectations that affect normative expectations in these two ways. (shrink)

The ongoing generation of expectations is fundamental to listeners’ experience of music, but research into types of statistical information that listeners extract from musical melodies has tended to emphasize transition probabilities and n‐grams, with limited consideration given to other types of statistical learning that may be relevant. Temporal associations between scale degrees represent a different type of information present in musical melodies that can be learned from musical corpora using expectation networks, a computationally simple method based on activation and (...) decay. Expectation networks infer the expectation of encountering one scale degree followed in the near (but not necessarily immediate) future by another given scale degree, with previous work suggesting that scale degree associations learned by expectation networks better predict listener ratings of pitch similarity than transition probabilities. The current work outlines how these learned scale degree associations can be combined to predict melodic continuations and tests the resulting predictions on a dataset of listener responses to a musical cloze task previously used to compare two other models of melodic expectation, a variable‐order Markov model (IDyOM) and Temperley's music‐theoretically motivated model. Under multinomial logistic regression, all three models explain significant unique variance in human melodic expectations, with coefficient estimates highest for expectation networks. These results suggest that generalized scale degree associations informed by both adjacent and nonadjacent relationships between melodic notes influence listeners’ melodic predictions above and beyond n‐gram context, highlighting the need to consider a broader range of statistical learning processes that may underlie listeners’ expectations for upcoming musical events. (shrink)

Previous studies of auditory expectation have focused on the expectedness perceived by listeners retrospectively in response to events. In contrast, this research examines predictive uncertainty —a property of listeners' prospective state of expectation prior to the onset of an event. We examine the information-theoretic concept of Shannon entropy as a model of predictive uncertainty in music cognition. This is motivated by the Statistical Learning Hypothesis, which proposes that schematic expectations reflect probabilistic relationships between sensory events learned implicitly (...) through exposure. Using probability estimates from an unsupervised, variable-order Markov model, 12 melodic contexts high in entropy and 12 melodic contexts low in entropy were selected from two musical repertoires differing in structural complexity (simple and complex). Musicians and non-musicians listened to the stimuli and provided explicit judgments of perceived uncertainty (explicit uncertainty). We also examined an indirect measure of uncertainty computed as the entropy of expectedness distributions obtained using a classical probe-tone paradigm where listeners rated the perceived expectedness of the final note in a melodic sequence (inferred uncertainty). Finally, we simulate listeners' perception of expectedness and uncertainty using computational models of auditory expectation. A detailed model comparison indicates which model parameters maximize fit to the data and how they compare to existing models in the literature. The results show that listeners experience greater uncertainty in high-entropy musical contexts than low-entropy contexts. This effect is particularly apparent for inferred uncertainty and is stronger in musicians than non-musicians. Consistent with the Statistical Learning Hypothesis, the results suggest that increased domain-relevant training is associated with an increasingly accurate cognitive model of probabilistic structure in music. (shrink)

This chapter asks two questions about the ethics of expectations: one about the nature of expectations, and one about the wrongs of expectations. On the first question, expectations involve a rich constellation of attitudes ranging from beliefs to also include imaginings, hopes, fears, and dreams. As a result, sometimes expectations act like predictions, like your expectation of rain tomorrow, sometimes prescriptions, like the expectation that your students will do the reading, sometimes like proleptic reasons like (...) the hope that your mentee will flourish, and sometimes expectations are peremptory in that they carry the force of moral law. Turning to the second question, given the multiple roles played by expectations it shouldn’t be surprising that there are also multiple ways expectations can be wrong to hold. Sometimes they wrong as beliefs do, e.g., doxastic wronging, and sometimes they result in alienation because of who holds that expectation of us. The upshot of this chapter is that getting clear on these potential ways expectations can wrong not only delivers an ethics of expectations that mirrors familiar discussions of the ethics of belief, but an ethics of expectations further opens the door for taking seriously an ethics of mental attitudes more generally. (shrink)

Linguistic predictions may be generated from and evaluated against a representation of events and referents described in the discourse. Compatible with this idea, recent work shows that predictions about novel noun phrases include their definiteness. In the current follow-up study, we ask whether people engage similar prediction-related processes for definite and indefinite referents. This question is relevant for linguistic theories that imply a processing difference between definite and indefinite noun phrases, typically because definiteness is thought to require a uniquely identifiable (...) referent in the discourse. We addressed this question in an event-related potential (ERP) study (N = 48) with preregistration of data acquisition, preprocessing, and Bayesian analysis. Participants read Dutch mini-stories with a definite or indefinite novel noun phrase (e.g., “het/een huis,” the/a house), wherein (in)definiteness of the article was either expected or unexpected and the noun was always strongly expected. Unexpected articles elicited enhanced N400s, but unexpectedly indefinite articles also elicited a positive ERP effect at frontal channels compared to expectedly indefinite articles. We tentatively link this effect to an antiuniqueness violation, which may force people to introduce a new referent over and above the already anticipated one. Interestingly, expectedly definite nouns elicited larger N400s than unexpectedly definite nouns (replicating a previous surprising finding) and indefinite nouns. Although the exact nature of these noun effects remains unknown, expectedly definite nouns may have triggered the strongest semantic activation because they alone refer to specific and concrete referents. In sum, results from both the articles and nouns clearly demonstrate that definiteness marking has a rapid effect on processing, counter to recent claims regarding definiteness processing. (shrink)

Promoting interpersonal helping among coworkers is an important aim for any organisation that cares about employee well-being. Drawing on guilt aversion hypothesis, this research focuses on the power of social expectations in promoting prosocial behaviour among employees and investigates the role of anticipated guilt for failing to meet coworkers’ expectations. In two preregistered studies, the effect of beneficiary expectation on benefactors’ anticipated guilt and intention to help was investigated. In Study 1, Japanese participants (n = 284) recalled a (...) situation when they helped a coworker spontaneously, and evaluated perceived beneficiary expectation to receive help, as well as anticipated guilt for not helping. Beneficiary expectation positively predicted anticipated guilt, and the effect was stronger when the beneficiary was a same-status colleague, and when interpersonal helping frequency in the organisation was low. Study 2 (n = 499) employed vignettes and manipulated beneficiary expectation. A mediational model revealed that beneficiary expectation leads to more anticipated guilt for not helping, which, in turn, increases employees’ intention to help. Together, these studies show that employees are sensitive to their coworkers’ expectations, and guilt-averse; therefore, interpersonal helping among employees may be promoted by establishing legitimate expectations of prosociality in the workplace. (shrink)

There is broad anthropological interest in understanding how people define “insiders” and “outsiders” and how this shapes their attitudes and behaviors toward others. As such, a suite of hypotheses has been proposed to account for the varying degrees of in-group preference between individuals and societies. We test three hypotheses related to material insecurity, pathogen stress, and views of gender equality among cross-sectional and longitudinal samples of young people in Ethiopia to explore stability and change in their preferences for coethnic spouses. (...) We show that food insecurity is associated with a greater likelihood of intolerant mate preferences. We also find that young people who hold more gender equitable attitudes tended to hold more tolerant mate preferences. Finally, we find no support for the hypothesis that expected pathogen exposure is associated with intolerant mate preferences. Our results most strongly support a material insecurity hypothesis of in-group bias, which assumes that uncertainty over meeting basic needs leads people to favor those in their in-group. As such, our findings join a small but growing group of studies that highlight the importance of material insecurity for understanding tolerance, xenophobia, in-group bias, and favoritism. (shrink)

Following in a psychological and musicological tradition beginning with Leonard Meyer, and continuing through David Huron, we present a functional, cognitive account of the phenomenon of expectation in music, grounded in computational, probabilistic modeling. We summarize a range of evidence for this approach, from psychology, neuroscience, musicology, linguistics, and creativity studies, and argue that simulating expectation is an important part of understanding a broad range of human faculties, in music and beyond.

Predictive processing models of perception take issue with standard models of perception as hierarchical bottom-up processing modulated by memory and attention. The predictive framework posits that the brain generates predictions about stimuli, which are matched to the incoming signal. Mismatches between predictions and the incoming signal – so-called prediction errors – are then used to generate new and better predictions until the prediction errors have been minimized, at which point a perception arises. Predictive models hold that all (...) bottom-up processes are signals conveying prediction errors to higher areas, which respond by updating their predictions. We take issue with this claim and argue that object recognition requires bottom-up processing that cannot be understood in terms of prediction errors. Along the way, we expand on previous work casting doubt on the framework's ability to account for attention. Specifically, we argue that the type of attention that allows us to rapidly extract the gist of an object or scene presents an additional challenge to the predictive approach. We conclude by considering how the framework may be augmented to avoid these problems. (shrink)

With this study, we aim to test the predictive relationships between determinants of major choice and academic expectations and to analyze gender differences, using six items of the Determinants of Major Choice Scale and the Academic Perceptions Questionnaire to assess AEs. A convenience sample of Portuguese and Spanish first-year students, mostly composed of women, was selected from two public universities. The invariance of the multivariate regression model with latent variables of the effect of DMC on AEs, with determinants (...) linked to Personal Characteristics and Mediating Agents as AE predictors, was tested across gender with LISREL. The invariance test of the multivariate regression model across gender fit the data well and revealed an equivalence of slopes between women and men, which allows a unique interpretation of the model’s predictive relationships for both genders. We also found statistically significant predictive relationships of PCs for six AE factors and MAs for five AE factors. The results showed theoretical relationships with the self-determination theory. At a practical level, they indicated the importance of PCs and MAs to design AE intervention programs in Higher Education institutions. (shrink)

Two decades ago, the introduction of the Implicit Association Test (IAT) sparked enthusiastic reactions. With implicit measures like the IAT, researchers hoped to finally be able to bridge the gap between self-reported attitudes on one hand and behavior on the other. Twenty years of research and several meta-analyses later, however, we have to conclude that neither the IAT nor its derivatives have fulfilled these expectations. Their predictive value for behavioral criteria is weak and their incremental validity over and (...) above self-report measures is negligible. In our review, we present an overview of explanations for these unsatisfactory findings and delineate promising ways forward. Over the years, several reasons for the IAT’s weak predictive validity have been proposed. They point to four potentially problematic features: First, the IAT is by no means a pure measure of individual differences in associations but suffers from extraneous influences like recoding. Hence, the predictive validity of IAT-scores should not be confused with the predictive validity of associations. Second, with the IAT, we usually aim to measure evaluation (“liking”) instead of motivation (“wanting”). Yet, behavior might be determined much more often by the latter than the former. Third, the IAT focuses on measuring associations instead of propositional beliefs and thus taps into a construct that might be too unspecific to account for behavior. Finally, studies on predictive validity are often characterized by a mismatch between predictor and criterion (e.g., while behavior is highly context-specific, the IAT usually takes into account neither situation nor domain). Recent research, however, also revealed advances addressing each of these problems, namely (1) procedural and analytical advances to control for recoding in the IAT, (2) measurement procedures to assess implicit wanting, (3) measurement procedures to assess implicit beliefs, and (4) approaches to increase the fit between implicit measures and behavioral criteria (e.g., by incorporating contextual information). Implicit measures like the IAT hold an enormous potential. In order to allow them to fulfill this potential, however, we have to refine our understanding of these measures, and we should incorporate recent conceptual and methodological advancements. This review provides specific recommendations on how to do so. (shrink)

In this paper, I discuss the relationship between bodily experiences in dreams and the sleeping, physical body. I question the popular view that dreaming is a naturally and frequently occurring real-world example of cranial envatment. This view states that dreams are functionally disembodied states: in a majority of dreams, phenomenal experience, including the phenomenology of embodied selfhood, unfolds completely independently of external and peripheral stimuli and outward movement. I advance an alternative and more empirically plausible view of dreams as weakly (...) phenomenally-functionally embodied states. The view predicts that bodily experiences in dreams can be placed on a continuum with bodily illusions in wakefulness. It also acknowledges that there is a high degree of variation across dreams and different sleep stages in the degree of causal coupling between dream imagery, sensory input, and outward motor activity. Furthermore, I use the example of movement sensations in dreams and their relation to outward muscular activity to develop a predictive processing account. I propose that movement sensations in dreams are associated with a basic and developmentally early kind of bodily self-sampling. This account, which affords a central role to active inference, can then be broadened to explain other aspects of self- and world-simulation in dreams. Dreams are world-simulations centered on the self, and important aspects of both self- and world-simulation in dreams are closely linked to bodily self-sampling, including muscular activity, illusory own-body perception, and vestibular orienting in sleep. This is consistent with cognitive accounts of dream generation, in which long-term beliefs and expectations, as well as waking concerns and memories play an important role. What I add to this picture is an emphasis on the real-body basis of dream imagery. This offers a novel perspective on the formation of dream imagery and suggests new lines of research. (shrink)

Trust is a kind of risky reliance on another person. Social scientists have offered two basic accounts of trust: predictive expectation accounts and staking (betting) accounts. Predictive expectation accounts identify trust with a judgment that performance is likely. Staking accounts identify trust with a judgment that reliance on the person’s performance is worthwhile. I argue (1) that these two views of trust are different, (2) that the staking account is preferable to the predictive expectation account on grounds (...) of intuitive adequacy and coherence with plausible explanations of action; and (3) that there are counterexamples to both accounts. I then set forward an additional necessary condition on trust, according to which trust implies a moral expectation. The content of the moral expectation is this: W hen A trusts B to do x, A ascribes an obligation to B to do x, and holds B to this obligation. This moral expectation account throws new light on some of the consequences of misplaced trust. I use the example of physicians’ defensive behavior to illustrate this final point. (shrink)

The two-factor theory (Davies, Coltheart, Langdon & Breen 2001; Coltheart 2007; Coltheart, Menzies & Sutton 2010) is an influential account of delusion formation. According to the theory, there are two distinct factors that are causally responsible for delusion formation. The first factor is supposed to explain the content of the delusion, while the second factor is supposed to explain why the delusion is adopted and maintained. Recently, another remarkable account of delusion formation has been proposed, in which the notion of (...) “prediction error” plays the central role (Fletcher & Frith 2009; Corlett, Krystal, Taylor & Fletcher 2009; Corlett, Taylor, Wang, Fletcher & Krystal 2010). According to this account, the prediction-error theory, delusions are formed in response to aberrant prediction-error signals, those signals that indicate a mismatch between expectation and actual experience. -/- In this chapter, we examine the relationship between the two-factor theory and the prediction-error theory in some detail. Our view is that the prediction-error theory does not have to be understood as a rival to the two-factor theory. We do not deny that there are some important differences between them. However, those differences are not as significant as they have been presented in the literature. Moreover, the core ideas of the prediction-error theory may be incorporated into the two- factor framework. For instance, the aberrant prediction-error signal that is posited by prediction-error theorists can be (or underlie) the first factor contributing to the formation of some delusions, and help explain the content of those delusions. Alternatively, the aberrant prediction-error signal can be (or underlie) the second factor, and help explain why the delusion is adopted and maintained. (shrink)

Brains, it has recently been argued, are essentially prediction machines. They are bundles of cells that support perception and action by constantly attempting to match incoming sensory inputs with top-down expectations or predictions. This is achieved using a hierarchical generative model that aims to minimize prediction error within a bidirectional cascade of cortical processing. Such accounts offer a unifying model of perception and action, illuminate the functional role of attention, and may neatly capture the special contribution of cortical processing (...) to adaptive success. This target article critically examines this approach, concluding that it offers the best clue yet to the shape of a unified science of mind and action. Sections 1 and 2 lay out the key elements and implications of the approach. Section 3 explores a variety of pitfalls and challenges, spanning the evidential, the methodological, and the more properly conceptual. The paper ends (sections 4 and 5) by asking how such approaches might impact our more general vision of mind, experience, and agency. (shrink)

Modular approaches to the architecture of the mind claim that some mental mechanisms, such as sensory input processes, operate in special-purpose subsystems that are functionally independent from the rest of the mind. This assumption of modularity seems to be in tension with recent claims that the mind has a predictive architecture. Predictive approaches propose that both sensory processing and higher-level processing are part of the same Bayesian information-processing hierarchy, with no clear boundary between perception and cognition. Furthermore, it (...) is not clear how any part of the predictive architecture could be functionally independent, given that each level of the hierarchy is influenced by the level above. Both the assumption of continuity across the predictive architecture and the seeming non-isolability of parts of the predictive architecture seem to be at odds with the modular approach. I explore and ultimately reject the predictive approach’s apparent commitments to continuity and non-isolation. I argue that predictive architectures can be modular architectures, and that we should in fact expect predictive architectures to exhibit some form of modularity. (shrink)

We often need to have beliefs about things on which we are not experts. Luckily, we often have access to expert judgements on such topics. But how should we form our beliefs on the basis of expert opinion when experts conflict in their judgments? This is the core of the novice/2-expert problem in social epistemology. A closely related question is important in the context of policy making: how should a policy maker use expert judgments when making policy in domains in (...) which she is not herself an expert? This question is more complex, given the messy and strategic nature of politics. In this paper we argue that the prediction with expert advice framework from machine learning provides helpful tools for addressing these problems. We outline conditions under which we should expert PWEA to be helpful and those under which we should not expect these methods to perform well. (shrink)

This paper examines racial discrimination and algorithmic bias in predictive policing algorithms (PPAs), an emerging technology designed to predict threats and suggest solutions in law enforcement. We first describe what discrimination is in a case study of Chicago’s PPA. We then explain their causes with Broadbent’s contrastive model of causation and causal diagrams. Based on the cognitive science literature, we also explain why fairness is not an objective truth discoverable in laboratories but has context-sensitive social meanings that need to (...) be negotiated through democratic processes. With the above analysis, we next predict why some recommendations given in the bias reduction literature are not as effective as expected. Unlike the cliché highlighting equal participation for all stakeholders in predictive policing, we emphasize power structures to avoid hermeneutical lacunae. Finally, we aim to control PPA discrimination by proposing a governance solution—a framework of a social safety net. (shrink)

In this paper, I discuss the strong thesis of cognitive penetrability (CPs), to wit, th at the perceptual states (P) of a subject (S) are pervasively influenced, affected, or caused by cognitive factors (C) as expectations, memories, thoughts, goals, and so on, at all levels of perceptual processing. I argue that following the predictive coding models of perception (PC), the strong thesis of cognitive penetrability is to be expected.

We introduce an expected-value theory of linguistic modality that makes reference to expected utility and a likelihood-based confirmation measure for deontics and epistemics, respectively. The account is a probabilistic semantics for deontics and epistemics, yet it proposes that deontics and epistemics share a common core modal semantics, as in traditional possible-worlds analysis of modality. We argue that this account is not only theoretically advantageous, but also has far-reaching empirical consequences. In particular, we predict modal versions of reasoning fallacies from the (...) heuristics and biases literature. Additionally, we derive the modal semantics in an entirely transparent manner, as it is based on the compositional semantics of Korean modal expressions that are morphosyntactically decomposed into a conditional and an evaluative predicate. (shrink)

Three studies investigated implicit brand attitudes and their relation to explicit attitudes, prod- uct usage, and product differentiation. Implicit attitudes were measured using the Implicit As- sociation Test (IAT; Greenwald, McGhee, & Schwartz, 1998). Study 1 showed expected differ- ences in implicit attitudes between users of two leading yogurt brands, also revealing significant correlations between IAT-measured implicit attitudes and explicit attitudes. In Study 2, users of two fast food restaurants (McDonald’s and Milk Bar) showed implicit attitudi- nal preference for their (...) favorite restaurant. In Study 3, implicit attitudes of users of two soft drinks (Coca-Cola and Pepsi) predicted brand preference, product usage, and brand recognition in a blind taste test. A meta-analytic combination of the three studies showed that the use of IAT measures increased the prediction of behavior relative to explicit attitude measures alone. (shrink)

Internal misconduct is a universal problem in prisons and affects the maintenance of social order. Consequently, correctional institutions often develop rehabilitation programs to reduce the likelihood of inmates committing internal offenses and criminal recidivism after release. Therefore, it is necessary to identify the profile of each offender, both for the appropriate indication of a rehabilitation program and the level of internal security to which he must be submitted. In this context, this work aims to discover the most significant characteristics in (...) predicting inmate misconduct from ML methods and the SHAP approach. A database produced in 2004 through the Survey of Inmates in State and Federal Correctional Facilities in the United States of America was used, which provides nationally representative data on prisoners from state and federal facilities. The predictive model based on Random Forest performed the best, thus, we applied the SHAP to it. Overall, the results showed that features related to victimization, type of crime committed, age and age at first arrest, history of association with criminal groups, education, and drug and alcohol use are most relevant in predicting internal misconduct. Thus, it is expected to contribute to the prior classification of an inmate on time, to use programs and practices that aim to improve the lives of offenders, their reintegration into society, and consequently, the reduction of criminal recidivism. (shrink)

In their target article, Lynch, Parke, and O’Malley argue against the quick application of causal, interventionist explanatory frameworks to microbiomes and their purported role in many disparate states, from obesity to anxiety. I think the authors have undersold the force of their argument. A careful consideration of the scope of their claims, made easier by a parallel drawn from the history of explanation in neuroscience, yields a productive pessimism: that causal explanations likely operate at the wrong level of analysis for (...) dynamic, distributed, Quineian entities like the microbiome. That is, we shouldn’t expect causal explanations for microbiomes at all—and this includes the authors’ own “microbiome success story” of C. difficile. Neuroscience, with its own computationally challenging, dynamic entity—the brain—may provide lessons for how to approach something like predictive control over the microbiome. (shrink)

Regina Fabry has proposed an intriguing marriage of enculturated cognition and predictive processing. I raise some questions for whether this marriage will work and warn against expecting too much from the predictive processing framework. Furthermore I argue that the predictive processes at a sub-personal level cannot be driving the innovations at a social level that lead to enculturated cognitive systems, like those explored in my target paper.

Life history theory predicts that greater extrinsic mortality will lead to earlier and higher fertility. To test this prediction, I examine the relationship between life expectancy at birth and several proxies for life history traits (ages at first sex and first marriage, total fertility rate, and ideal number of children), measured for both men and women. Data on sexual behaviors come from the Demographic and Health Surveys (DHS). Two separate samples are analyzed: a cross-sectional sample of 62 countries and a (...) panel sample that includes multiple cross-sectional panels from 48 countries. Multivariate regression analysis is used to control for potential confounding variables. The results provide only partial support for the predictions, with greater support among women than men. However, the prediction is not supported in sub-Saharan African countries, most likely owing to the nonequilibrium conditions observed in sub-Saharan Africa with respect to life expectancy. The applicability of the model to understanding HIV/AIDS risk behaviors is discussed. (shrink)

In the present paper, we will attempt to gain hints regarding the nature of tactile awareness in humans. At first, we will review some recent literature showing that an actual tactile experience can emerge in absence of any tactile stimulus (e.g., tactile hallucinations, tactile illusions). According to the current model of tactile awareness, we will subsequently argue that such (false) tactile perceptions are subserved by the same anatomo-functional mechanisms known to underpin actual perception. On these bases, we will discuss the (...) hypothesis that tactile awareness is strongly linked to expected rather than actual stimuli. Indeed, this hypothesis is in line with the notion that the human brain has a strong predictive, rather than reactive, nature. (shrink)

The mind is a powerful anticipatory device. It frequently makes predictions about the future, telling us not only how the world might or will be, but also how it should be - or better - how we would like it to be. This book explores anticipation-based emotions - the emotions associated with the interaction between 'what is' and 'what is not '.

Because they involve individual-level cognitive processes, psychological explanations of linguistic phenomena are in principle testable against individual behaviour. The present study draws on patterns of individual variation in corpus data to test explanations of productivity. Linguistic patterns are predicted to become more productive with higher type frequencies and lower token frequencies. This is because the formation of abstract mental representations is encouraged by varied types but counteracted by automation of high-frequency types. The predictions are tested for English -ly and -ness-derivation, (...) as used by 698 individual journalists in the New York Times Annotated Corpus and 171 members of Parliament in the Hansard Corpus. Linear regression is used to model individual variation in productivity, in relation to type and token frequency, as well as several other predictor variables. While the expected effects are observed, there is also robust evidence of an interaction effect between type and token frequency, indicating that productivity is highest for patterns with many types and not-too-infrequent tokens. This fits best with a view of entrenchment as both a conservative and creative force in language. Further, some variation remains irreducibly individual and is not explained by currently known predictors of productivity. (shrink)