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Record W2047058755 · doi:10.1037/a0032559

Affect spin and the emotion regulation process at work.

2013· article· en· W2047058755 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.

Bibliographic record

VenueJournal of Applied Psychology · 2013
Typearticle
Languageen
FieldPsychology
TopicEmotions and Moral Behavior
Canadian institutionsUniversity of Toronto
FundersArmy Research Institute for the Behavioral and Social Sciences
KeywordsAffect (linguistics)PsychologyTraitSocial psychologyExperience sampling methodCommunicationComputer science

Abstract

fetched live from OpenAlex

Regulating emotions is one of the most depleting activities that customer service employees are asked to do, but not all employees get burned out by the end of an emotionally laborious day. In the current study, affect spin-the trait variability of an individual's affective states-was hypothesized to increase strain and fatigue associated with emotion regulation, yet weaken the relation between recent strain and immediate fatigue. The authors examined these hypotheses in an experience sampling study of restaurant servers. Sixty-three servers completed surveys on 4 occasions during each of approximately 10 shifts (2,051 total surveys). Multilevel analyses supported the underlying model linking emotion regulation to fatigue at work as well as the hypothesized role of affect spin. Although affect spin reflects greater reactivity to affective events, it also provides some degree of a buffer from the fatiguing effects of these events.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.938
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.351
Teacher spread0.327 · 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