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Record W1975600556 · doi:10.1111/1467-6494.694156

The Need for Affect: Individual Differences in the Motivation to Approach or Avoid Emotions

2001· article· en· W1975600556 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Personality · 2001
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsWestern University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAffect (linguistics)PsychologyCognitive psychologySocial psychologyCommunication

Abstract

fetched live from OpenAlex

The present research developed and tested a new individual-difference measure of the need for affect, which is the motivation to approach or avoid emotion-inducing situations. The first phase of the research developed the need for affect scale. The second phase revealed that the need for affect is related to a number of individual differences in cognitive processes (e.g., need for cognition, need for closure), emotional processes (e.g., affect intensity, repression-sensitization), behavioral inhibition and activation (e.g., sensation seeking), and aspects of personality (Big Five dimensions) in the expected directions, while not being redundant with them. The third phase of the research indicated that, compared to people low in the need for affect, people high in the need for affect are more likely to (a) possess extreme attitudes across a variety of issues, (b) choose to view emotional movies, and (c) become involved in an emotion-inducing event (the death of Princess Diana). Overall, the results indicate that the need for affect is an important construct in understanding emotion-related processes.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.192
Threshold uncertainty score0.208

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.231
GPT teacher head0.399
Teacher spread0.168 · 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