MétaCan
Menu
Back to cohort
Record W1963808008 · doi:10.1177/0146167200266003

Control Motivation and Uncertainty: Information Processing or Avoidance in Moderate Depressives and Nondepressives

2000· article· en· W1963808008 on OpenAlexaff
Ann Walker, Richard M. Sorrentino

Bibliographic record

VenuePersonality and Social Psychology Bulletin · 2000
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsWestern University
Fundersnot available
KeywordsPsychologyInformation processingCertaintySocial psychologyCoping (psychology)Task (project management)Control (management)Developmental psychologyCognitive psychologyClinical psychology

Abstract

fetched live from OpenAlex

Two studies investigated the uncertainty orientation model of self-regulation as it relates to control motivation in moderate depressives and nondepressives. It was hypothesized that moderately depressed persons would be more likely than nondepressed persons to process information when control deprived, as opposed to nondeprived, only if they were uncertainty oriented. Certainty-oriented persons were expected to decrease information processing under these conditions. Participants differing in uncertainty orientation and depression level were assessed for information processing following control deprivation or no deprivation. In Study 1, desire for information about the deprivation task was assessed and participants were given a second performance task. In Study 2, information seeking was measured while reading about social outcomes. The expected three-factor interaction was found to be significant on measures of information seeking and performance in both studies. A model to represent these findings is proposed, as are implications for research on depression, coping, and control.

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)0.004
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.375
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

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

Citations26
Published2000
Admission routes1
Has abstractyes

Explore more

Same venuePersonality and Social Psychology BulletinSame topicBehavioral Health and InterventionsFrench-language works237,207