MétaCan
Menu
Back to cohort
Record W6926593206 · doi:10.24433/co.0432690.v2

Code for: Self-esteem, relationship threat, and dependency regulation: Independent replication of Murray, Rose, Bellavia, Holmes, and Kusche (2002) Study 3

2022· other· en· W6926593206 on OpenAlexaff

Bibliographic record

VenueCode Ocean · 2022
Typeother
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsWestern University
Fundersnot available
KeywordsDependency (UML)Empirical researchReplication (statistics)Situational ethicsField (mathematics)Code (set theory)Test (biology)

Abstract

fetched live from OpenAlex

Across three studies, Murray, Rose, Bellavia, Holmes, and Kusche (2002) found that low self-esteem individuals responded in a negative manner compared to those high in self-esteem in the face of relationship threat, perceiving their partners and relationships less positively. This was the first empirical support for the hypothesized dynamics of a dependency regulation perspective, and has had a significant impact on the field of relationship science. In the present research, we sought to reproduce the methods and procedures of Study 3 of Murray et al. (2002) to further test the two-way interaction between individual differences in self-esteem and situational relationship threat. Manipulation check effects replicated the original study, but no interaction between self-esteem and experimental condition was observed for any primary study outcomes.

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)0.003
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reproducibility · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.997
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0340.006

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 head0.030
GPT teacher head0.303
Teacher spread0.273 · 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 designNot applicable
DomainReproducibility
GenreSoftware

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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueCode OceanSame topicMicrobial infections and disease researchFrench-language works237,207