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Record W1524280487 · doi:10.22329/amr.v13i2.3020

An Item Response Theory Analysis Of The Self-Monitoring Scale

2010· article· en· W1524280487 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueApplied Multivariate Research · 2010
Typearticle
Languageen
FieldDecision Sciences
TopicPsychometric Methodologies and Testing
Canadian institutionsnot available
Fundersnot available
KeywordsItem response theoryExtraversion and introversionPsychologyScale (ratio)Construct (python library)Classical test theoryPsychometricsRasch modelConstruct validityCognitive psychologySocial psychologyDevelopmental psychologyPersonalityBig Five personality traitsComputer science

Abstract

fetched live from OpenAlex

The Self-Monitoring Scale (SMS) was investigated utilizing item response theory (IRT). First, IRT models that constrained each of the subscale items to have equal discrimination were fitted to the three subscales of the SMS (Acting, Extraversion, and Other-Directedness). These models were then contrasted with separate models that allowed the discriminations to be estimated freely. For all three subscales, model comparison tests of significance indicated that the unconstrained models were a better fit. Thus, the items of each subscale are differentially related to their respective underlying construct. Implications and recommendations are offered for future psychometric development and implementation of the SMS.

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)0.095
metaresearch head score (Gemma)0.125
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.718
Threshold uncertainty score0.932

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0950.125
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.015
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.001
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 head0.445
GPT teacher head0.565
Teacher spread0.120 · 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