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Record W4386472711 · doi:10.33921/liuj2948

Examination of the interaction effect of stress in the relationship between value congruence and intrinsic work motivation

2023· article· en· W4386472711 on OpenAlexvenueno aff
Madeleine Gaudet, Denis Lajoie

Bibliographic record

VenueJournal of Interpersonal Relations Intergroup Relations and Identity · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsModerationPsychologyCongruence (geometry)Social psychologyEquivalence (formal languages)Intrinsic motivationValue (mathematics)MathematicsStatisticsPure mathematics

Abstract

fetched live from OpenAlex

The purpose of this study is to observe whether workplace stress could act as a moderator in the relationship between value congruence and intrinsic motivation. According to theoretical perspectives, stress-related psychological demands should attenuate the positive effect of value congruence-related psychological resources on motivation. 294 subjects participated in this study by completing questionnaires on our three variables of interest on the Prolific platform. The results did not show an interaction effect by stress on the relationship between value congruence and intrinsic motivation. Moreover, an equivalence test indicated that the moderation effect size was too small to influence the practical level. In conclusion, the hypothesis postulating a moderating link of stress on the relationship between value congruence and intrinsic motivation was not confirmed.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.021
GPT teacher head0.279
Teacher spread0.258 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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