Familiar Categories Research Articles

The Distance Between the Story Character and the Reader: Evidencing the Impact of Familiarity in Children’s Storybooks

Familiarity is a crucial element in narrative fiction reading for children, playing a significant role in social learning from storybooks. Nevertheless, distinct studies greatly vary in their interpretation of what renders a storybook familiar to a child, researchers’ methods for measuring familiarity, and how researchers link familiarity to reading outcomes. This integrative review synthesized the principal ways in which researchers define and measure familiarity when investigating the impacts of storybooks on children’s social learning outcomes. In particular, we derived four key definition categories of familiarity from the current empirical literature: personal relevance, anthropomorphism, social relevance and realism. We specified which outcomes are most impacted by which type of familiarity, in terms of broader outcomes (e.g. transfer of factual information from storybooks examined for anthropomorphism and realism) or specific learning effects (e.g. story comprehension with storybooks modified for personal relevance). Overall, our findings suggest that it is not familiarity per se, but rather its extent (how much the content of a storybook is familiar to the child prior to reading), that holds importance for social learning outcomes. The theoretical assumption of the distance hypothesis provides a compelling explanation for this finding.

Religious Differences in Physical and Mental Health among Israeli Jews: Findings from the Global Flourishing Study.

Numerous studies have identified religious correlates of health indicators, but relatively few have been conducted among Jewish populations in Israel or the diaspora. This study investigates the possibility of a religious gradient in physical and mental health and well-being across the familiar categories of Jewish religious identity and observance in Israel: hiloni (secular), masorti lo dati (traditional, non-religious), masorti (traditional), dati (religious or Orthodox), and charedi (ultra-Orthodox). Data are from Jewish respondents aged 18 and over (N = 2916) from the Israeli sample of the new, 22-nation Global Flourishing Study, which used stratified, probability-based sampling and assessed demographic, socioeconomic, political, religious, health-related, and other variables. This analysis investigated religious differences in nine indicators of physical and mental health and well-being among Israeli Jews. Using a strategy of one-way ANOVA and ANCOVA, adjusting for complex sampling design components, a statistically significant "dose-response"-like gradient was found for eight of the outcome measures, validated by additional multiple comparison tests. For four "positively" worded indicators (physical and mental health, happiness, and life satisfaction), scores increased consistently from the hiloni to the charedi categories. For four of five "negatively" worded indicators (bodily pain, depression, anxiety, and suffering), scores decreased across the same categories. Results withstood adjusting for effects of age, sex, education, marital status, urbanicity, income, and nativity (whether born in Israel). Among Israeli Jews, greater religiousness was associated with higher levels of health and well-being and lower levels of somatic and psychological distress.

Becoming word meaning experts: Infants' processing of familiar words in the context of typical and atypical exemplars.

How do infants become word meaning experts? This registered report investigated the structure of infants' early lexical representations by manipulating the typicality of exemplars from familiar animal categories. 14- to 18-month-old infants (N = 84; 51 female; M = 15.7 months; race/ethnicity: 64% White, 8% Asian, 2% Hispanic, 1% Black, and 23% multiple categories; participating 2022-2023) were tested on their ability to recognize typical and atypical category exemplars after hearing familiar basic-level category labels. Infants robustly recognized both typical (d = 0.79, 95% CI [0.54, 1.03]) and atypical (d = 0.70, 95% CI [0.46, 0.94]) exemplars, with no significant difference between typicality conditions (d = 0.14, 95% CI [-0.08, 0.35]). These results support a broad-to-narrow account of infants' early word meanings. Implications for the role of experience in the development of lexical knowledge are discussed.

@Brand-to-@brand: the value co-creating impact of social media interactions on consumer–brand evaluations

PurposeConspicuously absent from the branding literature is research on the brand-to-brand (Br2Br) interface enabled by social media. The author proposes how networked brands-as-actors integrate their resources as Br2Br interactions that co-create consumer–brand value. As a secondary contribution, the author provides an empirical baseline exploration of the value co-creating impact of Br2Br interactions on consumer–brand evaluations and social media engagement.Design/methodology/approachThree streams of research aid in conceptualizing the value co-creating process of Br2Br interactions. A follow-up exploratory study uses a controlled Br2Br interaction stimulus in a 2 × 2 × 2 between-subjects design, where brand familiarity and product category complementarity are manipulated, and interaction spillover effects are analyzed using structural equation modeling.FindingsThe author finds Br2Br interactions positively affect consumer–brand evaluations and social media engagement likelihood. Spillover effects of these interactions are symmetric for consumer–brand evaluations for both brands. However, brand familiarity moderates the effects of Br2Br interactions on consumer–brand evaluations.OriginalityThe author lays the groundwork for future research on the complexities of Br2Br interactions – including brand personality conflict, interaction duration and paratextual language – and the boundary conditions for Br2Br and brand-to-consumer relationships.

Deviation from typical organic voices best explains a vocal uncanny valley

The uncanny valley describes the negative evaluation of near humanlike artificial entities. Previous research with synthetic and real voices failed to find an uncanny valley of voices. This may have been due to an incomplete selection of stimuli. In Experiment 1 (n = 50), synthetic, normal, and deviating voices (distorted and pathological) were rated on uncanniness and human likeness and categorized as human or non-human. Results showed a non-monotonic function when the uncanniness was plotted against human likeness indicative of an uncanny valley. However, the shape could be divided into two monotonic functions based on voice type (synthetic vs deviating). Categorization ambiguity could not predict voice uncanniness but moderated the effect of realism on uncanniness. Experiment 2 (n = 35) found that perceived organicness, animacy, and mind attribution of voices significantly moderated the effect of realism on uncanniness. Results indicate a vocal uncanny valley driven by deviations from typical human voices. While voices can fall into an uncanny valley, synthetic voices successfully escape it. Finally, the results support the account that uncanniness is caused by deviations from familiar categories, rather than categorical ambiguity or the misattribution of mind or animacy.

The role of perceptual similarities in determining the asymmetric mixed-category advantage.

Considering working memory capacity limitations, representing all relevant data simultaneously is unlikely. What remains unclear is why some items are better remembered than others when all data are equally relevant. While trying to answer this question, the literature has identified a pattern named the mixed-category benefit in which performance is enhanced when presenting stimuli from different categories as compared to presenting a similar number of items that all belong to just one category. Moreover, previous studies revealed an asymmetry in performance while mixing certain categories, suggesting that not all categories benefit equally from being mixed. In a series of three change-detection experiments, the present study investigated the role of low-level perceptual similarities between categories in determining the mixed-category asymmetric advantages. Our primary conclusion is that items' similarity at the perceptual level has a significant role in the asymmetric performance in the mixed-category phenomenon. We measured sensitivity (d') to detect a change between sample and test displays and found that the mixed-category advantage dropped when the mixed categories shared basic features. Furthermore, we found that sensitivity to novel items was impaired when presented with another category sharing its basic features. Finally, increasing the encoding interval improved performance for the novel items, but novel items' performance was still impaired when these items were mixed with another category that shared their basic features. Our findings highlight the significant role low-level similarities play in the asymmetric mixed-category performances, for both novel and familiar categories. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Searching near and far: The attentional template incorporates viewing distance.

According to theories of visual search, observers generate a visual representation of the search target (the "attentional template") that guides spatial attention toward target-like visual input. In real-world vision, however, objects produce vastly different visual input depending on their location: your car produces a retinal image that is 10 times smaller when it is parked 50 compared to 5 m away. Across four experiments, we investigated whether the attentional template incorporates viewing distance when observers search for familiar object categories. On each trial, participants were precued to search for a car or person in the near or far plane of an outdoor scene. In "search trials," the scene reappeared and participants had to indicate whether the search target was present or absent. In intermixed "catch-trials," two silhouettes were briefly presented on either side of fixation (matching the shape and/or predicted size of the search target), one of which was followed by a probe-stimulus. We found that participants were more accurate at reporting the location (Experiments 1 and 2) and orientation (Experiment 3) of probe stimuli when they were presented at the location of size-matching silhouettes. Thus, attentional templates incorporate the predicted size of an object based on the current viewing distance. This was only the case, however, when silhouettes also matched the shape of the search target (Experiment 2). We conclude that attentional templates for finding objects in scenes are shaped by a combination of category-specific attributes (shape) and context-dependent expectations about the likely appearance (size) of these objects at the current viewing location. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A linear exponential comonad in s-finite transition kernels and probabilistic coherent spaces

This paper concerns a stochastic construction of probabilistic coherent spaces by employing novel ingredients (i) linear exponential comonad arising properly in the measure-theory (ii) continuous orthogonality between measures and measurable functions.A linear exponential comonad is constructed over a symmetric monoidal category of transition kernels, relaxing Markov kernels of Panangaden's stochastic relations into s-finite kernels. The model supports an orthogonality in terms of an integral between measures and measurable functions, which can be seen as a continuous extension of Girard-Danos-Ehrhard's linear duality for probabilistic coherent spaces. The orthogonality is formulated by a Hyland-Schalk double glueing construction, into which our measure theoretic monoidal comonad structure is accommodated. As an application to countable measurable spaces, a dagger compact closed category is obtained, whose double glueing gives rise to the familiar category of probabilistic coherent spaces.

Locating what comes to mind in empirically derived representational spaces

Real-world judgements and decisions often require choosing from an open-ended set of options which cannot be exhaustively considered before a choice is made. Recent work has found that the options people do consider tend to have particular features, such as high historical value. Here, we pursue the idea that option generation during decision making may reflect a more general mechanism for calling things to mind, by which relevant features in a context-appropriate representational space guide what comes to mind. In this paper, we evaluate this proposal primarily based on what comes to mind in different familiar categories. We first introduce an empirical approach for deriving the space of features that people use to represent items in a particular category and for locating the category members that come to mind within that space. We show that in both familiar and ad hoc categories, a category member’s location along certain dimensions of the derived feature space predicts its likelihood of coming to mind. Next, we show that category members from these feature space locations come to mind by default in a way that is somewhat impervious to conscious control. We then demonstrate that the extent to which a given dimension is a predictor of what comes to mind within a category is related to how relevant that feature is for representing the category in question, using a novel measure of general feature relevance. Finally, we illustrate the usefulness of this framework in the context of a decision making task. We close with the proposal that people call category members to mind according to their location in representational space, specifically based on the predicted usefulness of considering category members with particular features.

Effects of prior knowledge on brain activation and functional connectivity during memory retrieval

Previous studies have shown that the ventral medial prefrontal cortex (vmPFC) plays an important role in schema-related memory. However, there is an intensive debate to what extent the activation of subregions of the hippocampus is involved in retrieving schema-related memory. In addition, it is unclear how the functional connectivity (FC) between the vmPFC and the hippocampus, as well as the connectivity of the vmPFC with other regions, are modulated by prior knowledge (PK) during memory retrieval over time. To address these issues, participants learned paragraphs that described features of each unfamiliar word from familiar and unfamiliar categories (i.e., high and low PK conditions) 20 min, 1 day, and 1 week before the test. They then performed a recognition task to judge whether the sentences were old in the scanner. The results showed that the activation of the anterior-medial hippocampus (amHPC) cluster was stronger when the old sentences with high (vs. low) PK were correctly retrieved. The activation of the posterior hippocampus (pHPC) cluster, as well as the vmPFC, was stronger when the new sentences with high (vs. low) PK were correctly rejected (i.e., CR trials), whereas the cluster of anterior-lateral hippocampus (alHPC) showed the opposite. The FC of the vmPFC with the amHPC and perirhinal cortex/inferior temporal gyrus was stronger in the high (vs. low) PK condition, whereas the FC of the vmPFC with the alHPC, thalamus and frontal regions showed the opposite for the CR trials. This study highlighted that different brain networks, which were associated with the vmPFC, subregions of the hippocampus and cognitive control regions, were responsible for retrieving the information with high and low PK.

ENGLISH NEOLOGISMS OF ANCIENT GREEK AND LATIN ORIGIN IN THE FIELD OF PSYCHOLOGY

In our rapidly developing world, people often need to create words to name new concepts. The process of creating a new word is actually very complex and consists of a number of stages that are mostly carried out at the subconscious level. People need to understand the role of a newly encountered phenomenon in the world around them and how that phenomenon will be classified within the framework of the already familiar categories. Another problem is the choice of the outer (phonetic) form of the newly created word, which is mainly based on the categorization process of the new phenomenon encountered by a person. This paper is aimed at studying the role of morphemes of Ancient Greek and Latin origin in the process of coining neologisms in the field of psychology. Psychology is a rapidly developing branch of science, and consequently new words need to be coined frequently. In the paper, we tried to reveal what kind of categorization processes take place when creating new words, and how these processes affect the external phonetic composition of given neologisms, and in particular, why Ancient Greek or Latin morphemes are chosen for coining neologisms in the field of psychology.

An object's categorizability impacts whether infants encode surface features into their object representations.

Infants encode the surface features of simple, unfamiliar objects (e.g., red triangle) and the categorical identities of familiar, categorizable objects (e.g., car) into their representations of these objects. We asked whether 16-18-month-olds ignore non-diagnostic surface features (e.g., color) in favor of encoding an object's categorical identity (e.g., car) when objects are from familiar categories. In Experiment 1 (n=18), we hid a categorizable object inside an opaque box. In No Switch trials, infants retrieved the object that was hidden. In Switch trials, infants retrieved a different object: an object from a different category (Between-Category-Switch trials) or a different object from the same category (Within-Category-Switch trials). We measured infants' subsequent searching in the box. Infants' pattern of searching suggested that only infants who completed a Within-Category-Switch trial as their first Switch trial encoded objects' surface features, and an exploratory analysis suggested that infants who completed a Between-Category-Switch trial as their first Switch trial only encoded objects' categories. In Experiment 2 (n=18), we confirmed that these results were due to objects' categorizability. These results suggest infants may tailor the way they encode categorizable objects depending on which object dimensions are perceived to be task relevant.

Beyond ‘globalizing’ care: Care ethics for the pluriverse

The questions and issues that make up the field of global ethics have, for several decades now, largely been understood through the binary framework of ‘cosmopolitanism’ and ‘communitarianism’. Despite the widespread criticism of the limitations of this dualism, and some attempts to ‘qualify or hyphenate core terms’ it has proven ‘remarkably difficult to escape or transcend’ the cosmopolitanism-communitarianism framework (Sutch, 2018: 35). Maggie Fitzgerald’s new book, Care and the Pluriverse: Rethinking Global Ethics, manages not only manages to escape these familiar categories, but to break new ground in global ethics.

The influence of the stimulus category on the characteristics of eye movements in visual search

Introduction. The speed and efficiency of visual search are important characteristics of the activities of a significant range of specialists working with visual information. Specialists have carefully studied the features of visual search from the point of view of cognitive psychology and in connection with the modeling of oculomotor activity. It has been shown that its effectiveness and the parameters of search eye movements are influenced by both stimulation factors and some cognitive factors (features of the subject's preset, the influence of previous search stages, etc.). We assume that the search features are also related to how well a person represents the desired stimulus: whether it belongs to a familiar semantic category, how accurate and unambiguous its visual representation is.
 The study aims to explore the relationship between the parameters of eye movements in visual search and the features of the mental representation of the target object.
 Materials and methods. We have created sets of stimuli belonging to different semantic categories, characterized by different accuracy of mental representations, but having similar sensory qualities. Each object (both the target stimulus and the distractor) in the search field was a black circle on a white background with four black segments inside. The segments formed one of three configurations: a) a face; b) a Roman numeral; c) a random configuration. The study participants were asked to find in a matrix of 84 objects a specific target stimulus belonging to one of the three specified categories. The scientists recorded the participant's eye movements during the search.
 Results. The results of the study generally confirmed the hypothesis about the relationship of search characteristics with the category of the target object. The smallest number of errors, the minimum duration of fixation and the maximum amplitude of saccades characterized the search for Roman numerals — objects with a well-formed and well-defined visual representation. The most difficult, as expected, was the search for objects representing random configurations of segments.
 Limitations. Since the study was largely exploratory in nature, the results obtained require clarification on a wider sample. It is possible that the characteristics of the search were influenced by such a factor not controlled in the study as the configuration of the lines, namely, the presence or absence of their intersections, which should be taken into account in further work.
 Conclusions. The better the visual representation of the target object is formed, the more successful its search is. In this case, eye movements are characterized by a shorter duration of fixation and a higher frequency of saccades of greater amplitude.
 Ethics. The study was conducted in compliance with the ethical principles set out in the Helsinki Declaration of the World Medical Association, all participants gave voluntary informed consent.

The Design of E-Commerce System to Increase Sales Productivity of Home Industry in Indonesia

The household industry is the foundation of the existing home industry in Indonesia. It is categorized as a type of Small and Medium Enterprises (MSMEs) that significantly influence the Gross Domestic Product (GDP) ratio by up to approximately 10%. Since the pandemic of Covid-19, the home industry has increasingly stretched, especially in culinary and home craft products. The internet is one of the efforts to increase household industry sales. The household industry needs e-commerce to be a container for marketing its products. In this paper, we design an e-commerce system to support the sales productivity of the household industry in Indonesia. This study's e-commerce system or application is developed through some crucial stages. The stages are analysis through a questionnaire that represents needs in the field, selection of business models, namely B2B models with Virtual Storefront, marketplace concentrators, and lastly, Information Broker. Our infrastructure is determined for e-commerce development, and then strategy analysis is done using portfolio analysis, SWOT analysis, and competitor analysis. Based on the proposed strategy, we made a prototype as a designed e-commerce system that can increase sales for household businesses in cities in Indonesia. Important features in our proposed e-commerce system can accommodate many sellers or the household industry to establish relationships with many buyers based on geographical location, product search features based on closest positions or by city, and product categorization by familiar categories with household products.Â

Using Event-Related Potentials (ERP) to identify the purchase intention of a consumer for familiar brands

Several neurological processes are undergoing on a conscious and subconscious level every time a consumer likes or dislikes a product. There is presently significant research in Consumer Neuroscience based on consumer behaviour and understanding of these processes. In this study, we have used Electroencephalography (EEG) and Event-Related Potentials (ERP) to capture consumer responses to highly familiar product images. EEG analysed from the 27 participants was used to extract P1, N1, P300, N400 and Late Posterior components. The analysis showed that the early ERP components viz., P1, N1 and P300 can differentiate between consumer liking and disliking of products. In contrast, the late ERP components N400 and Late Posterior components could not differentiate in the highly familiar product category. The results indicate that after continuous exposure, consumer preference towards highly-familiar products occurs as a part of automatic, unconscious mental processes irrespective of the product properties. Further research in this direction can test for the transference of consumer preference: from a conscious mental process to a subconscious mental process due to excessive and continuous product exposure and marketing repetition. Our study demonstrates that consumer behaviour in response to highly-familiar products can be classified using early ERP components only.

Instruments, agents, and artificial intelligence: novel epistemic categories of reliability

Deep learning (DL) has become increasingly central to science, primarily due to its capacity to quickly, efficiently, and accurately predict and classify phenomena of scientific interest. This paper seeks to understand the principles that underwrite scientists’ epistemic entitlement to rely on DL in the first place and argues that these principles are philosophically novel. The question of this paper is not whether scientists can be justified in trusting in the reliability of DL. While today’s artificial intelligence exhibits characteristics common to both scientific instruments and scientific experts, this paper argues that the familiar epistemic categories that justify belief in the reliability of instruments and experts are distinct, and that belief in the reliability of DL cannot be reduced to either. Understanding what can justify belief in AI reliability represents an occasion and opportunity for exciting, new philosophy of science.

The deviation-from-familiarity effect: Expertise increases uncanniness of deviating exemplars.

Humanlike entities deviating from the norm of human appearance are perceived as strange or uncanny. Explanations for the eeriness of deviating humanlike entities include ideas specific to human or animal stimuli like mate selection, avoidance of threat or disease, or dehumanization; however, deviation from highly familiar categories may provide a better explanation. Here it is tested whether experts and novices in a novel (greeble) category show different patterns of abnormality, attractiveness, and uncanniness responses to distorted and averaged greebles. Greeble-trained participants assessed the abnormality, attractiveness, uncanniness of normal, averaged, and distorted greebles and their responses were compared to participants who had not previously seen greebles. The data show that distorted greebles were more uncanny than normal greebles only in the training condition, and distorted greebles were more uncanny in the training compared to the control condition. In addition, averaged greebles were not more attractive than normal greebles regardless of condition. The results suggest uncanniness is elicited by deviations from stimulus categories of expertise rather than being a purely biological human- or animal-specific response.

Constellations with range and IS-categories

Constellations are asymmetric generalisations of categories. Although they are not required to possess a notion of range, many natural examples do. These include commonly occurring constellations related to concrete categories (since they model surjective morphisms), and also others arising from quite different sources, including from well-studied classes of semigroups . We show how constellations with a well-behaved range operation are nothing but ordered categories with restrictions. We characterise abstractly those categories that are canonical extensions of constellations with range, as so-called IS-categories. Such categories contain distinguished subcategories of insertions (which are monomorphisms) and surjections (in general different to the epimorphisms) such that each morphism admits a unique factorisation into a surjection followed by an insertion. Most familiar concrete categories are IS-categories, and we show how some of the well-known properties of these categories arise from the fact that they are IS-categories. For appropriate choices of morphisms in each, the category of IS-categories is shown to be equivalent to the category of constellations with range.

From Unicorn Data Scientist to Key Roles in Data Science: Standardizing Roles

The lack of an agreed-upon classification of job roles related to data science is causing much confusion that is challenging to the industry, educational sector, and practitioners. Prior work in this area has considered different aspects from different fields or points of view and has shown that more detail is needed in subcategorizing data science professionals. However, other prior work has also shown that avoiding the detailed subcategorization leads to challenging problems, for example, the pursuit of the elusive ‘data science unicorns.’ In this article, we target a simplification of prior work and an anchor categorization of job roles with clear definitions and expectations from each. We achieve this through analysis of survey results, LinkedIn profiles and job descriptions, and in-depth interviews with managing and hiring executives in data science. We also use our judgment as long-term practitioners and employers of data scientists to provide a practice-guided view of the problem.Our analysis has led to a simplification into three key role families with complementary skills: data analyst, data scientist, and data engineer. We believe this anchor categorization helps resolve several problems, including recruiting, forming, training, managing, and retaining effective data science teams. Although we realize there are and will continue to be many variations of these proposed anchor roles, this simplification is an effective tool to bypass the data science unicorn issue, and it can be used as a basis to establish more specialized or domain-specific roles. The combined skills in these role categories converge on the body of knowledge specification from the Initiative for Analytics and Data Science Standards (IADSS) data science knowledge framework (Fayyad & Hamutcu, 2020). The concise and familiar role categories simplify the problem and decompose it into more solvable subchallenges. We describe the essential knowledge required for each role and how, when, and in what ways it can be varied and extended. This description helps align expectations and serves as a step to tackle the pressing issue of training, evaluating, and building effective data science teams.