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Record W2064861158 · doi:10.1037/a0019130

The effect of negative feedback on tension and subsequent performance: The main and interactive effects of goal content and conscientiousness.

2010· article· en· W2064861158 on OpenAlexaff
Anna M. Cianci, Howard J. Klein, Gerard Seijts

Bibliographic record

VenueJournal of Applied Psychology · 2010
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsWestern University
Fundersnot available
KeywordsConscientiousnessPsychologyModerationTask (project management)Social psychologyPersonalityBig Five personality traitsCognitive psychologyDevelopmental psychologyExtraversion and introversion

Abstract

fetched live from OpenAlex

The purpose of this experiment was to examine the interplay of goal content, conscientiousness, and tension on performance following negative feedback. Undergraduate students were assigned either a learning or performance goal and then were provided with false feedback indicating very poor performance on the task they performed. After assessing tension, participants performed the task again with the same learning or performance goal. A mediated moderation model was tested, and results were supportive of our hypotheses. Specifically, individuals assigned a learning goal experienced less tension and performed better following negative feedback than individuals assigned a performance goal. Individuals high in conscientiousness experienced greater tension than individuals low in conscientiousness. Conscientiousness and goal content interacted in relating to both tension and performance, with tension as a mediator, such that high conscientiousness amplified the detrimental effect of a performance goal on tension following negative feedback leading to lower performance. High conscientiousness facilitated performance for participants with a learning goal.

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)0.001
metaresearch head score (Gemma)0.012
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.014
GPT teacher head0.305
Teacher spread0.292 · 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

Citations221
Published2010
Admission routes1
Has abstractyes

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