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Record W2808980008 · doi:10.1177/0033294118783917

The Conscientious Responders Scale Helps Researchers Verify the Integrity of Personality Questionnaire Data

2018· article· en· W2808980008 on OpenAlexaff
Zdravko Marjanovic, Lisa Bajkov, Jennifer MacDonald

Bibliographic record

VenuePsychological Reports · 2018
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsThompson Rivers UniversityConcordia University of Edmonton
Fundersnot available
KeywordsScale (ratio)PsychologyCronbach's alphaPsychometricsGeneralizability theoryPersonalityClinical psychologyReactanceTest validityCalifornia Psychological InventoryPersonality Assessment InventorySocial psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

is a five-item embeddable validity scale that differentiates between conscientious and indiscriminate responding in personality-questionnaire data (CR & IR). This investigation presents further evidence of its validity and generalizability across two experiments. Study 1 tests its sensitivity to questionnaire length, a known cause of IR, and tries to provoke IR by manipulating psychological reactance. As expected, short questionnaires produced higher Conscientious Responders Scale scores than long questionnaires, and Conscientious Responders Scale scores were unaffected by reactance manipulations. Study 2 tests concerns that the Conscientious Responders Scale's unusual item content could potentially irritate and baffle responders, ironically increasing rates of IR. We administered two nearly identical questionnaires: one with an embedded Conscientious Responders Scale and one without the Conscientious Responders Scale. Psychometric comparisons revealed no differences across questionnaires' means, variances, interitem response consistencies, and Cronbach's alphas. In sum, the Conscientious Responders Scale is highly sensitive to questionnaire length-a known correlate of IR-and can be embedded harmlessly in questionnaires without provoking IR or changing the psychometrics of other measures.

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 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)0.011
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.597
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.007
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.281
GPT teacher head0.496
Teacher spread0.216 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
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

Citations10
Published2018
Admission routes1
Has abstractyes

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