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Record W1529164518

The Oxford companion to emotion and the affective sciences

2009· preprint· en· W1529164518 on OpenAlex
David Sander, Klaus R. Scherer

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueArchive ouverte UNIGE (University of Geneva) · 2009
Typepreprint
Languageen
FieldArts and Humanities
TopicHistory of Science and Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsAffect (linguistics)CasualPsychologyCognitionJudgementPerceptionAction (physics)ParagraphCognitive scienceCognitive psychologySocial psychologyEpistemologyComputer scienceCommunication
DOInot available

Abstract

fetched live from OpenAlex

Few areas have witnessed the type of growth we have seen in the affective sciences in the past decades. Across psychology, philosophy, economics, and neuroscience, there has been an explosion of interest in the topic of emotion and affect. Comprehensive, authoritative, up-to-date, and easy-to-use, the new Oxford Companion to Emotion and the Affective Sciences is an indispensable resource for all who wish to find out about theories, concepts, methods, and research findings in this rapidly growing interdisciplinary field - one that brings together, amongst others, psychologists, neuroscientists, social scientists, philosophers, and historians. Organized by alphabetical entries, and presenting brief definitions, concise overviews, and encyclopaedic articles (all with extensive references to relevant publications), this Companion lends itself to casual browsing by non-specialists interested in the fascinating phenomena of emotions, moods, affect disorders, and personality as well as to focused search for pertinent information by students and established scholars in the field. Not only does the book provide entries on affective phenomena, but also on their neural underpinnings, their cognitive antecedents and the associated responses in physiological systems, facial, vocal, and bodily expressions, and action tendencies. Numerous entries also consider the role of emotion in society and social behavior, as well as in cognitive processes such as those critical for perception, attention, memory, judgement and decision-making. The volume has been edited by a group of internationally leading authorities in the respective disciplines consisting of two editors (David Sander and Klaus Scherer) as well as group of 11 associate editors (John T. Cacioppo, Tim Dalgleish, Robert Dantzer, Richard J. Davidson, Ronald B. de Sousa, Phoebe C. Ellsworth, Nico Frijda, George Loewenstein, Paula M. Niedenthal, Peter Salovey, and Richard A. Shweder). The members of the editorial board have commissioned and reviewed contributions from major experts on specific topics. In addition to comprehensive coverage of technical terms and fundamental issues, the volume also highlights current debates that inform the ongoing research process. In addition, the Companion contains a wealth of material on the role of emotion in applied domains such as economic behaviour, music and arts, work and organizational behaviour, family interactions and group dynamics, religion, law and justice, and societal change. Highly accessible and wide-ranging, this book is a vital resource for scientists, students, and professionals eager to obtain a rapid, conclusive overview on central terms and topics and anyone wanting to learn more about the mechanisms underlying the emotions dominating many aspects of our lives. Contributors to this volume - John T. Cacioppo, University of Chicago, UK Tim Dalgleish, Cambridge University, UK Robert Dantzer, University of Illinois at Urbana- Champaign, USA Richard J. Davidson, University of Wisconsin Madison, USA Ronald B. de Sousa, University of Toronto, Canada Phoebe C. Ellsworth, University of Michigan, USA Nico Frijda, University of Amsterdam, The Netherlands George Loewenstein, Carnegie Mellon University, USA Paula M. Niedenthal, University of Clermont-Ferrand II / CNRS, France Peter Salovey, Yale University, USA Richard A. Shweder, University of Chicago, USA

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.207
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it