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Record W2138135002 · doi:10.1177/0013164406299101

An Item Response Theory Examination of Two Popular Goal Orientation Measures

2007· article· en· W2138135002 on OpenAlexaff
Leifur Geir Hafsteinsson, John J. Donovan, B. Tyson Breland

Bibliographic record

VenueEducational and Psychological Measurement · 2007
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsMarriott International (Canada)
Fundersnot available
KeywordsGoal orientationConstruct (python library)Orientation (vector space)Item response theoryPsychologyScale (ratio)PsychometricsConstruct validityCognitive psychologySocial psychologyComputer scienceDevelopmental psychologyMathematics

Abstract

fetched live from OpenAlex

The current study used item response theory to provide a detailed examination of the psychometric properties of scores from two goal orientation instruments popular in the work motivation literature: Button, Mathieu, and Zajac (1996) and VandeWalle (1997). In general, the results of these analyses indicated that all scales except Button et al.'s (1996) Learning Goal Orientation (LGO) scale suffered from low levels of measurement precision. The Performance Goal Orientation scales contained a number of items that were of limited informational value. Button et al.'s (1996) LGO scale performed adequately but only for those with low to moderately high standings on the construct. Implications of these results and recommendations for future research on the goal orientation construct are presented.

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)0.038
metaresearch head score (Gemma)0.138
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.200

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.138
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.118
GPT teacher head0.398
Teacher spread0.280 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations29
Published2007
Admission routes1
Has abstractyes

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