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Record W3095522485 · doi:10.1037/pspa0000362

Metamotivational beliefs about intrinsic and extrinsic motivation.

2023· article· en· W3095522485 on OpenAlexafffund
Candice Hubley, Jessica Edwards, David B. Miele, Abigail A. Scholer

Bibliographic record

VenueJournal of Personality and Social Psychology · 2023
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of CanadaJames S. McDonnell Foundation
KeywordsPsychologyIntrinsic motivationTask (project management)NormativeCognitive psychologyContext (archaeology)Social psychologySelf-determination theoryGoal theoryRelevance (law)Cognitive evaluation theory

Abstract

fetched live from OpenAlex

= 3,544), participants provided beliefs about the utility of different types of motivation-regulation strategies: strategies that enhance one's interest and enjoyment in a task versus strategies that focus on the value associated with task outcomes (self-relevance strategies and reward strategies). Across all studies, participants recognized that the adaptiveness of these strategies depends on the nature of the task being completed. Consistent with an understanding of normative task-motivation fit, participants generally reported that interest-enhancing strategies were more useful for open-ended tasks and that reward strategies were more useful for closed-ended tasks; however, in some studies, participants reported that reward strategies were equally useful across task types (Studies 2, 3, and 5). More normatively accurate beliefs were associated with more normatively accurate consequential behavioral choices (Study 6) and better task performance (Study 7). We discuss the implications of these results for theories of motivation and self-regulation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.716
Threshold uncertainty score0.924

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)0.0010.000

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 head0.151
GPT teacher head0.443
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 teacher head, 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

Citations18
Published2023
Admission routes2
Has abstractyes

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