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Record W3122189339

Blue Porches: Finding the Limits of External Validity of the Endowment Effect

2020· preprint· en· W3122189339 on OpenAlexaff
Gharad Bryan, Matthew J. Grant, Kareem Haggag, Dean Karlan, Meredith Startz, Christopher Udry

Bibliographic record

VenueLondon School of Economics and Political Science Research Online (London School of Economics and Political Science) · 2020
Typepreprint
Languageen
FieldSocial Sciences
TopicPsychology of Social Influence
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsEndowmentEndowment effectContext (archaeology)Test (biology)EconomicsExternal validityProtocol (science)MicroeconomicsEconometricsPsychologySocial psychologyPolitical scienceMedicineLawGeographyBiology
DOInot available

Abstract

fetched live from OpenAlex

We test whether the endowment effect holds in an experiment conducted with children during Halloween trick-or-treating. We do not find evidence of the endowment effect in this context and with this experimental protocol.

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)0.032
metaresearch head score (Gemma)0.167
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.968
Threshold uncertainty score0.170

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.167
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.009
Scholarly communication0.0020.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.160
GPT teacher head0.443
Teacher spread0.283 · 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.

Study designObservational
DomainMethods
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

Citations0
Published2020
Admission routes1
Has abstractyes

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