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Record W2069130763 · doi:10.1509/jmkr.43.1.15

Understanding Regulatory Fit

2006· article· en· W2069130763 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 Marketing Research · 2006
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsRegulatory focus theoryFeelingPsychologyOrientation (vector space)Social psychologyFocus (optics)Process (computing)Outcome (game theory)Cognitive psychologyComputer scienceMicroeconomicsEconomics

Abstract

fetched live from OpenAlex

The authors focus on three critical areas of future research on regulatory fit. First, they focus on how regulatory orientation is sustained. The authors argue that there are two distinct approaches that bring about the “just-right feeling”: (1) a process-based approach that involves the interaction between regulatory orientation and decision-making processes and (2) an outcome-based approach that involves the interaction between regulatory orientation and the framed outcomes offered. Second, the authors discuss possible boundary conditions of regulatory fit effects, highlighting the apparent paradoxical role of involvement. They suggest that the antecedents that give rise to regulatory fit (e.g., lowered motivation) can differ from its consequences (e.g., increased motivation). Third, the authors discuss broader implications of regulatory fit, proposing three possible mechanisms by which regulatory fit can lead to improved physical health and discussing the degree to which the just-right feeling plays a role in goal-sustaining experiences related to subjective well-being (e.g., flow).

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)0.020
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 score0.848
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.502
GPT teacher head0.526
Teacher spread0.025 · 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