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Record W2207149291 · doi:10.3389/fpsyg.2015.01562

Scientific integrity in research methods

2015· article· en· W2207149291 on OpenAlexafffund
Jordan Richard Schoenherr

Bibliographic record

VenueFrontiers in Psychology · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsCarleton University
FundersOttawa HospitalOttawa Hospital Research Institute
KeywordsPsychologyFront (military)Research integrityApplied psychologyCognitive scienceEngineering ethics

Abstract

fetched live from OpenAlex

Recent cases of research misconduct have prompted psychologists to suggest that there is too much vulnerability in the research process (e.g., Regardless of whether this is the case, ensuring the integrity of a discipline requires a clear understanding of what conventions and norms define the research process. In what follows, I consider the research integrity curriculum of North American psychology. In particular, I will claim that a major impediment to ensuring responsible research practices is an underspecified and understudied curriculum.

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)0.667
metaresearch head score (Gemma)0.768
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.977
Threshold uncertainty score0.411

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.6670.768
Meta-epidemiology (narrow)0.0020.004
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0090.007
Science and technology studies0.0110.069
Scholarly communication0.0190.020
Open science0.0080.015
Research integrity0.0230.031
Insufficient payload (model declined to judge)0.0070.004

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 head0.699
GPT teacher head0.699
Teacher spread0.001 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
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

Citations7
Published2015
Admission routes2
Has abstractyes

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