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Record W2532227323 · doi:10.1177/1948550616671401

The “Holding-Out” Effect

2016· article· en· W2532227323 on OpenAlexaff
Olya Bullard, Rajesh V. Manchanda, A.V. Sizykh

Bibliographic record

VenueSocial Psychological and Personality Science · 2016
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of ManitobaUniversity of Winnipeg
Fundersnot available
KeywordsRegulatory focus theoryPsychologyPreferenceSequence (biology)Promotion (chess)Social psychologyMechanism (biology)Focus (optics)Cognitive psychologyMicroeconomicsEconomicsEpistemology

Abstract

fetched live from OpenAlex

This research examines the influence of regulatory focus on preference formation for sequentially presented choice alternatives. Across three experiments, we demonstrate the “holding-out” effect exhibited by prevention-focused individuals who tend to undervalue earlier options in a sequence, examine more options, and select an option encountered later in a sequence compared to promotion-focused individuals. We suggest and provide initial evidence that the mechanism underlying the holding-out effect is an inability to externally generate a comparison point in the beginning of a sequence, which negatively affects evaluations made by prevention-focused individuals.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.927
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.003
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 head0.154
GPT teacher head0.498
Teacher spread0.344 · 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; both teacher heads agree on what is shown here.

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

Citations7
Published2016
Admission routes1
Has abstractyes

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