Rationale and development of a general population well-being measure: Psychometric status of the GP-CORE in a student sample
Bibliographic record
Abstract
This paper presents the rationale, development, and psychometric status of a non-clinical self-report measure for the general population (GP) – including students – derived from the Clinical Outcomes in Routine Evaluation-Outcome Measure (CORE-OM) and hence termed the GP-CORE. In contrast to the CORE-OM, the GP-CORE does not comprise items denoting high-intensity of presenting problems or risk and thereby increases its acceptability in a non-clinical population. Uniquely, over half the items in the GP-CORE are positively keyed. Analyses showed the GP-CORE to have good reliability, to distinguish between clinical and non-clinical populations, and have convergent validity against the full version. Norms for student populations are presented. It is suggested that the GP-CORE has considerable utility as a means of tapping the psychological well being of students and can then interface with counselling and mental health services using the CORE-OM.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.034 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".