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Record W2584999368 · doi:10.1177/1474704917690740

Bidding to Commit

2017· article· en· W2584999368 on OpenAlex
Pat Barclay

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEvolutionary Psychology · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicExperimental Behavioral Economics Studies
Canadian institutionsUniversity of Guelph
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBiddingCommitAction (physics)BattleSocial psychologyDovePsychologyIrrational numberEconomicsMicroeconomicsMarketingBusinessComputer science

Abstract

fetched live from OpenAlex

Economists and biologists have both theorized that individuals can benefit from committing to courses of action because it forces others to concede a greater share of any surpluses, but little experimental work has tested the actual benefits of such a strategy and people's willingness to so "tie their hands." Participants played a Battle-of-the-Sexes (Experiment 1) or Hawk-Dove game (Experiment 2), where one member of each pair could not change his or her action once played (committed), whereas the other could change actions in response (uncommitted). Committed players were more likely to achieve their preferred outcomes. When bidding to select roles, most participants preferred to be committed rather than uncommitted, though they bid slightly less than the committed role was actually worth. These results provide empirical support for people's willingness to use commitment to their advantage and show that commitment devices (e.g., "irrational" emotions) can bring long-term benefits.

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)0.000
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.680
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.105
GPT teacher head0.469
Teacher spread0.364 · 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