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Record W2180735259 · doi:10.1177/2158244014545964

The Conscientious Responders Scale

2014· article· en· W2180735259 on OpenAlex

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.

Bibliographic record

VenueSAGE Open · 2014
Typearticle
Languageen
FieldDecision Sciences
TopicPsychometric Methodologies and Testing
Canadian institutionsYork UniversityThompson Rivers University
Fundersnot available
KeywordsScale (ratio)Reliability (semiconductor)Item response theoryPsychologyOddsClinical psychologyPsychometricsStatisticsSocial psychologyMedicineApplied psychologyLogistic regressionMathematics

Abstract

fetched live from OpenAlex

This investigation introduces a novel tool for identifying conscientious responders (CRs) and random responders (RRs) in psychological inventory data. The Conscientious Responders Scale (CRS) is a five-item validity measure that uses instructional items to identify responders. Because each item instructs responders exactly how to answer that particular item, each response can be scored as either correct or incorrect. Given the long odds of answering a CRS item correctly by chance alone on a 7-point scale (14.29%), we reasoned that RRs would answer most items incorrectly, whereas CRs would answer them correctly. This rationale was evaluated in two experiments in which CRs’ CRS scores were compared against RRs’ scores. As predicted, results showed large differences in CRS scores across responder groups. Moreover, the CRS correctly classified responders as either conscientious or random with greater than 93% accuracy. Implications for the reliability and effectiveness of the CRS are discussed.

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)0.028
metaresearch head score (Gemma)0.115
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.943
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0280.115
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0020.000
Open science0.0030.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.434
GPT teacher head0.514
Teacher spread0.080 · 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