Scrolling through fake news: The effect of presentation order on misinformation retention.

Sharing information in real time leaves little room for double-checking. This leads to an abundance of low-quality information that might later need to be corrected and provides a foundation on which false beliefs can arise. Today, the general population often consults digital media platforms for news content. Because of the sheer amount of news articles and the various ways digital media platforms organize material, readers may encounter news articles with faulty content and their subsequent corrections in various orders. They might read the misinformation before the corrected version or vice versa. We conducted two studies in which participants were presented with two reports of a news event: one report that included a piece of misinformation and one report in which that misinformation was retracted. The order in which the two reports were encountered was manipulated. In Study 1, the retraction contained an explicit reminder of the misinformation; in Study 2, it did not. Neither Study 1 nor Study 2 found an effect of presentation order on misinformation reliance. These findings run counter to predictions by those accounts of the continued influence effect that suggest a better encoding of retractions and subsequent lesser reliance on misinformation when retractions are encountered first. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Similarity-based reasoning in conceptual spaces.

Whereas the validity of deductive inferences can be characterized in terms of their logical form, this is not true for all inferences that appear pre-theoretically valid. Nonetheless, philosophers have argued that at least some of those inferences-sometimes called "similarity-based inferences" -can be given a formal treatment with the help of similarity spaces, which are mathematical spaces purporting to represent human similarity judgments. In these inferences, we conclude that a given property pertains to a category of items on the grounds that the same property pertains to a similar category of items. We look at a specific proposal according to which the strength of such inferences is a function of the distance, as measured in the appropriate similarity space, between the category referenced in the premise and the category referenced in the conclusion. We report the outcomes of three studies that all support the said proposal.

Teaching open and reproducible scholarship: a critical review of the evidence base for current pedagogical methods and their outcomes.

In recent years, the scientific community has called for improvements in the credibility, robustness and reproducibility of research, characterized by increased interest and promotion of open and transparent research practices. While progress has been positive, there is a lack of consideration about how this approach can be embedded into undergraduate and postgraduate research training. Specifically, a critical overview of the literature which investigates how integrating open and reproducible science may influence student outcomes is needed. In this paper, we provide the first critical review of literature surrounding the integration of open and reproducible scholarship into teaching and learning and its associated outcomes in students. Our review highlighted how embedding open and reproducible scholarship appears to be associated with (i) students' scientific literacies (i.e. students' understanding of open research, consumption of science and the development of transferable skills); (ii) student engagement (i.e. motivation and engagement with learning, collaboration and engagement in open research) and (iii) students' attitudes towards science (i.e. trust in science and confidence in research findings). However, our review also identified a need for more robust and rigorous methods within pedagogical research, including more interventional and experimental evaluations of teaching practice. We discuss implications for teaching and learning scholarship.

The idiosyncratic nature of how individuals perceive, represent, and remember their surroundings and its impact on learning-based generalization.

The current study adopted a multimodal assessment approach to map the idiosyncratic nature of how individuals perceive, represent, and remember their surroundings and to investigate its impact on learning-based generalization. During an online differential conditioning paradigm, participants (n = 105) learned the pairing between a blue color patch (CS +) and an outcome (i.e., shock symbol) and the unpairing between a green color patch and the same outcome. After the learning task, the generalization of outcome expectancies was assessed to 14 stimuli spanning the entire blue-green color spectrum. Hereafter, a stimulus identification task assessed the ability to correctly identify the CS + among this stimulus range. Continuous and binary color category membership judgments of the stimuli were assessed preconditioning. We found that a response model with color perception and identification performance as sole predictors was preferred to contemporary approaches that use stimulus as a predictor. Interestingly, incorporating interindividual differences in color perception, CS identification, and color categories significantly improved the models' ability to account for different generalization patterns. Our findings suggest that insight into the idiosyncratic nature of how individuals perceive, represent, and remember their surroundings provides exciting opportunities to understand post-learning behaviors better. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Taking a Closer Look at the Bayesian Truth Serum.

Over the past few decades, psychology and its cognate disciplines have undergone substantial scientific reform, ranging from advances in statistical methodology to significant changes in academic norms. One aspect of experimental design that has received comparatively little attention is incentivization, i.e., the way that participants are rewarded and incentivized monetarily for their participation in experiments and surveys. While incentive-compatible designs are the norm in disciplines like economics, the majority of studies in psychology and experimental philosophy are constructed such that individuals' incentives to maximize their payoffs in many cases stand opposed to their incentives to state their true preferences honestly. This is in part because the subject matter is often self-report data about subjective topics, and the sample is drawn from online platforms like Prolific or MTurk where many participants are out to make a quick buck. One mechanism that allows for the introduction of an incentive-compatible design in such circumstances is the Bayesian Truth Serum (BTS; Prelec, 2004), which rewards participants based on how surprisingly common their answers are. Recently, Schoenegger (2021) applied this mechanism in the context of Likert-scale self-reports, finding that the introduction of this mechanism significantly altered response behavior. In this registered report, we further investigate this mechanism by (1) attempting to directly replicate the previous result and (2) analyzing if the Bayesian Truth Serum's effect is distinct from the effects of its constituent parts (increase in expected earnings and addition of prediction tasks). We fail to find significant differences in response behavior between participants who were simply paid for completing the study and participants who were incentivized with the BTS. Per our pre-registration, we regard this as evidence in favor of a null effect of up to V = .1 and a failure to replicate but reserve judgment as to whether the BTS mechanism should be adopted in social science fields that rely heavily on Likert-scale items reporting subjective data, seeing that smaller effect sizes might still be of practical interest and results may differ for items different from the ones we studied. Further, we provide weak evidence that the prediction task itself influences response distributions and that this task's effect is distinct from an increase in expected earnings, suggesting a complex interaction between the BTS' constituent parts and its truth-telling instructions.

A Comparison of the Spatial Arrangement Method and the Total-Set Pairwise Rating Method for Obtaining Similarity Data in the Conceptual Domain.

We compare two methods for obtaining similarity data in the conceptual domain. In the Spatial Arrangement Method (SpAM), participants organize stimuli on a computer screen so that the distance between stimuli represents their perceived dissimilarity. In Total-Set Pairwise Rating Method (PRaM), participants rate the (dis)similarity of all pairs of stimuli on a Likert scale. In each of three studies, we had participants indicate the similarity of four sets of conceptual stimuli with either PRaM or SpAM. Studies 1 and 2 confirm two caveats that have been raised for SpAM. (i) While SpAM takes significantly less time to complete than PRaM, it yields less reliable data than PRaM does. (ii) Because of the spatial manner in which similarity is measured in SpAM, the method is biased against feature representations. Despite these differences, averaging SpAM and PRaM dissimilarity data across participants yields comparable aggregate data. Study 3 shows that by having participants only judge half of the pairs in PRaM, its duration can be significantly reduced, without affecting the dissimilarity distribution, but at the cost of a smaller reliability. Having participants arrange multiple subsets of the stimuli does not do away with the spatial bias of SpAM.

Age biases the judgment rather than the perception of an ambiguous figure.

Older participants who are briefly presented with the 'my wife/mother-in-law' ambiguous figure estimate its age to be higher than young participants do. This finding is thought to be the result of a subconscious social group bias that influences participants' perception of the figure. Because people are better able to recognize similarly aged individuals, young participants are expected to perceive the ambiguous figure as a young woman, while older participants are more likely to recognize an older lady. We replicate the difference in age estimates, but find no relationship between participants' age and their perception of the ambiguous figure. This leads us to conclude that the positive relationship between participants' age and their age estimates of the ambiguous 'my wife/mother-in-law' figure is better explained by the own-age anchor effect, which holds that people use their own age as a yard stick to judge the age of the figure, regardless of whether the young woman or the older lady is perceived. Our results disqualify the original finding as an example of cognitive penetrability: the participants' age biases their judgment of the ambiguous figure, not its perception.

Lexicosemantic, affective, and distributional norms for 1,000 Dutch adjectives.

The research of the word is still very much the research of the noun. Adjectives have been largely overlooked, despite being the second-largest word class in many languages and serving an important communicative function, because of the rich, nuanced qualifications they afford. Adjectives are also ideally suited to study the interface between cognition and emotion, as they naturally cover the entire range of lexicosemantic variables such as imageability (infinite-green), and affective variables such as valence (sad-happy). We illustrate this by showing how the centrality of words in the mental lexicon varies as a function of the words' affective dimensions, using newly collected norms for 1,000 Dutch adjectives. The norms include the lexicosemantic variables age of acquisition, familiarity, concreteness, and imageability; the affective variables valence, arousal, and dominance; and a variety of distributional variables, including network statistics resulting from a large-scale word association study. The norms are freely available from https://osf.io/nyg8v/, for researchers studying adjectives specifically or for whom adjectives constitute convenient stimuli to study other topics, such as vagueness, inference, spatial cognition, or affective word processing.

Revealing Criterial Vagueness in Inconsistencies.

Sixty undergraduate students made category membership decisions for each of 132 candidate exemplar-category name pairs (e.g., chess - Sports) in each of two separate sessions. They were frequently inconsistent from one session to the next, both for nominal categories such as Sports and Fish, and ad hoc categories such as Things You Rescue from a Burning House. A mixture model analysis revealed that several of these inconsistencies could be attributed to criterial vagueness: participants adopting different criteria for membership in the two sessions. This finding indicates that categorization is a probabilistic process, whereby the conditions for applying a category label are not invariant. Individuals have various functional meanings of nominal categories at their disposal and entertain competing goals for ad hoc categories.

Age-Related Degree and Criteria Differences in Semantic Categorization.

Individual differences in semantic categorization are commonplace. Individuals apply a word like SPORTS to different instances because they employ different conditions for category membership (vagueness in criteria) or because they differ regarding the extent to which they feel the term can be applied given fixed conditions (vagueness in degree). Three individuals may, for instance, disagree as to whether chess and hiking are SPORTS, because one believes SPORTS are competitive in nature, while the other two require SPORTS to be effortful (vagueness in criteria). On the basis of whether they consider hiking sufficiently effortful or not, the latter two individuals might still disagree as to whether to call it a SPORT (vagueness in degree). We investigated whether there are systematic age-related differences in semantic categorization by analyzing the categorization decisions of 1,868 adults for eight semantic categories with a formal model that allows the two sources of categorization differences to be disentangled. We found that young and older adults assess instances differently with respect to the categorization conditions and that older adults employ a lower threshold for category membership than young adults do. We recommend that these criteria and degree differences are taken into account in studies of age-related semantic processing.

Typicality and Graded Membership in Dimensional Adjectives.

This paper concerns an investigation of the manner in which typicality constrains graded membership in antonymous dimensional adjectives such as short/tall and cheap/expensive using the conceptual spaces framework. In this framework, items are organized in a space comprised of one or more dimensions along which they can be compared. The items' graded membership is established by their relative proximity in this space to the prototypical instances of contrasting concepts. Because dimensional adjectives can be applied to an indefinite variety of things and grammatically have no upper bound to serve as cognitive reference point, they have been argued to lack prototypes. We present the results of an empirical study showing that the conceptual spaces framework can nevertheless be extended successfully to dimensional adjectives by complementing them with a comparison class argument (such as short/tall for an adult man and cheap/expensive for a smartphone), allowing participants to retrieve meaningful prototypical instances, which can be used to establish membership degree. Since dimensional adjectives are subjective, we investigate how the framework can accommodate interindividual variability in membership degree judgments. We find that the predictions of the framework significantly improve if prototypical instances themselves are assumed to come with a gradient instead of being considered equally typical, thereby providing a more fine-grained account of typicality and furthering the development of the conceptual spaces framework.

Predicting Lexical Norms: A Comparison between a Word Association Model and Text-Based Word Co-occurrence Models.

In two studies we compare a distributional semantic model derived from word co-occurrences and a word association based model in their ability to predict properties that affect lexical processing. We focus on age of acquisition, concreteness, and three affective variables, namely valence, arousal, and dominance, since all these variables have been shown to be fundamental in word meaning. In both studies we use a model based on data obtained in a continued free word association task to predict these variables. In Study 1 we directly compare this model to a word co-occurrence model based on syntactic dependency relations to see which model is better at predicting the variables under scrutiny in Dutch. In Study 2 we replicate our findings in English and compare our results to those reported in the literature. In both studies we find the word association-based model fit to predict diverse word properties. Especially in the case of predicting affective word properties, we show that the association model is superior to the distributional model.

Caveats for the spatial arrangement method: Comment on Hout, Goldinger, and Ferguson (2013).

The gold standard among proximity data collection methods for multidimensional scaling is the (dis)similarity rating of pairwise presented stimuli. A drawback of the pairwise method is its lengthy duration, which may cause participants to change their strategy over time, become fatigued, or disengage altogether. Hout, Goldinger, and Ferguson (2013) recently made a case for the Spatial Arrangement Method (SpAM) as an alternative to the pairwise method, arguing that it is faster and more engaging. SpAM invites participants to directly arrange stimuli on a computer screen such that the interstimuli distances are proportional to psychological proximity. Based on a reanalysis of the Hout et al. (2013), data we identify three caveats for SpAM. An investigation of the distributional characteristics of the SpAM proximity data reveals that the spatial nature of SpAM imposes structure on the data, invoking a bias against featural representations. Individual-differences scaling of the SpAM proximity data reveals that the two-dimensional nature of SpAM allows individuals to only communicate two dimensions of variation among stimuli properly, invoking a bias against high-dimensional scaling representations. Monte Carlo simulations indicate that in order to obtain reliable estimates of the group average, SpAM requires more individuals to be tested. We conclude with an overview of considerations that can inform the choice between SpAM and the pairwise method and offer suggestions on how to overcome their respective limitations.

The role of corpus size and syntax in deriving lexico-semantic representations for a wide range of concepts.

One of the most significant recent advances in the study of semantic processing is the advent of models based on text and other corpora. In this study, we address what impact both the quantitative and qualitative properties of corpora have on mental representations derived from them. More precisely, we evaluate models with different linguistic and mental constraints on their ability to predict semantic relatedness between items from a vast range of domains and categories. We find that a model based on syntactic dependency relations captures significantly less of the variability for all kinds of words, regardless of the semantic relation between them or their abstractness. The largest difference was found for concrete nouns, which are commonly used to assess semantic processing. For both models we find that limited amounts of data suffice in order to obtain reliable predictions. Together, these findings suggest new constraints for the construction of mental models from corpora, both in terms of the corpus size and in terms of the linguistic properties that contribute to mental representations.

Problems of reliability and validity with similarity derived from category fluency.

This study aims to assess the reliability and the validity of exemplar similarity derived from category fluency tasks. A homogeneous sample of 21 healthy participants completed a category fluency task twice with an interval of one week. They also rated pairs comprised of the most frequently generated exemplars in terms of similarity. Similarities were derived from the fluency data by determining the average distance between generated exemplars and correcting it for repetitions and response sequence length. We calculated the correlation between the similarities derived from the two sessions of the fluency task and between the derived similarities and the directly rated similarities. Spatial representations of the similarities were constructed using multidimensional scaling to visualize the differences between both sessions of the fluency task and the pairwise rating task. We find that the derived similarities are not stable in time and show little correspondence with directly rated similarities. The differences between similarities derived from category fluency tasks in healthy participants, indicate that similar differences between healthy controls and patients with mental disorders, do not necessarily point to a semantic impairment of the latter, but rather reflect the unreliability of the data.

Deriving semantic structure from category fluency: clustering techniques and their pitfalls.

Assessing verbal output in category fluency tasks provides a sensitive indicator of cortical dysfunction. The most common metrics are the overall number of words produced and the number of errors. Two main observations have been made about the structure of the output, first that there is a temporal component to it with words being generated in spurts, and second that the clustering pattern may reflect a search for meanings such that the 'clustering' is attributable to the activation of a specific semantic field in memory. A number of sophisticated approaches to examining the structure of this clustering have been developed, and a core theme is that the similarity relations between category members will reveal the mental semantic structure of the category underlying an individual's responses, which can then be visualized by a number of algorithms, such as MDS, hierarchical clustering, ADDTREE, ADCLUS or SVD. Such approaches have been applied to a variety of neurological and psychiatric populations, and the general conclusion has been that the clinical condition systematically distorts the semantic structure in the patients, as compared to the healthy controls. In the present paper we explore this approach to understanding semantic structure using category fluency data. On the basis of a large pool of patients with schizophrenia (n = 204) and healthy control participants (n = 204), we find that the methods are problematic and unreliable to the extent that it is not possible to conclude that any putative difference reflects a systematic difference between the semantic representations in patients and controls. Moreover, taking into account the unreliability of the methods, we find that the most probable conclusion to be made is that no difference in underlying semantic representation exists. The consequences of these findings to understanding semantic structure, and the use of category fluency data, in cortical dysfunction are discussed.

A mixture approach to vagueness and ambiguity.

When asked to indicate which items from a set of candidates belong to a particular natural language category inter-individual differences occur: Individuals disagree which items should be considered category members. The premise of this paper is that these inter-individual differences in semantic categorization reflect both ambiguity and vagueness. Categorization differences are said to be due to ambiguity when individuals employ different criteria for categorization. For instance, individuals may disagree whether hiking or darts is the better example of sports because they emphasize respectively whether an activity is strenuous and whether rules apply. Categorization differences are said to be due to vagueness when individuals employ different cut-offs for separating members from non-members. For instance, the decision to include hiking in the sports category or not, may hinge on how strenuous different individuals require sports to be. This claim is supported by the application of a mixture model to categorization data for eight natural language categories. The mixture model can identify latent groups of categorizers who regard different items likely category members (i.e., ambiguity) with categorizers within each of the groups differing in their propensity to provide membership responses (i.e., vagueness). The identified subgroups are shown to emphasize different sets of category attributes when making their categorization decisions.

Uncovering contrast categories in categorization with a probabilistic threshold model.

A contrast category effect on categorization occurs when the decision to apply a category term to an entity not only involves a comparison between the entity and the target category but is also influenced by a comparison of the entity with 1 or more alternative categories from the same domain as the target. Establishing a contrast category effect on categorization in natural language categories has proven to be laborious, especially when the categories concerned are natural kinds situated at the superordinate level of abstraction. We conducted 3 studies with these categories to look for an influence on categorization of both similarity to the target category and similarity to a contrast category. The results are analyzed with a probabilistic threshold model that assumes categorization decisions arise from the placement of threshold criteria by individual categorizers along a single scale that holds the experimental stimuli. The stimuli's positions along the scale are shown to be influenced by similarity to both target and contrast. These findings suggest that the prevalence of contrast category effects on categorization might have been underestimated. Additional analyses demonstrate how the proposed model can be employed in future studies to systematically investigate the origins of contrast category effects on categorization.

Raising argument strength using negative evidence: a constraint on models of induction.

Both intuitively, and according to similarity-based theories of induction, relevant evidence raises argument strength when it is positive and lowers it when it is negative. In three experiments, we tested the hypothesis that argument strength can actually increase when negative evidence is introduced. Two kinds of argument were compared through forced choice or sequential evaluation: single positive arguments (e.g., "Shostakovich's music causes alpha waves in the brain; therefore, Bach's music causes alpha waves in the brain") and double mixed arguments (e.g., "Shostakovich's music causes alpha waves in the brain, X's music DOES NOT; therefore, Bach's music causes alpha waves in the brain"). Negative evidence in the second premise lowered credence when it applied to an item X from the same subcategory (e.g., Haydn) and raised it when it applied to a different subcategory (e.g., AC/DC). The results constitute a new constraint on models of induction.