MétaCan
Menu
Back to cohort
Record W2519235992 · doi:10.1016/j.jesp.2015.11.004

Replications with MTurkers who are naïve versus experienced with academic studies: A comment on Connors, Khamitov, Moroz, Campbell, and Henderson (2015)

2016· article· en· W2519235992 on OpenAlexaff
Sanford E. DeVoe, Julian House

Bibliographic record

VenueJournal of Experimental Social Psychology · 2016
Typearticle
Languageen
FieldComputer Science
TopicNeural Networks and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPython (programming language)Computer scienceArtificial intelligenceHuman intelligenceArtificial neural networkCognitionTree (set theory)Bayesian probabilityMachine learningPsychologyCognitive scienceMathematics

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.056
metaresearch head score (Gemma)0.324
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reproducibility · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.944
Threshold uncertainty score0.298

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0560.324
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0090.007
Scholarly communication0.0040.006
Open science0.0070.004
Research integrity0.0200.015
Insufficient payload (model declined to judge)0.0070.003

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 head0.080
GPT teacher head0.412
Teacher spread0.332 · 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
DomainReproducibility
GenreCommentary

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

Citations13
Published2016
Admission routes1
Has abstractno

Explore more

Same venueJournal of Experimental Social PsychologySame topicNeural Networks and ApplicationsFrench-language works237,207