Development of the Global Self-Esteem Measure: A Pilot Study
Bibliographic record
Abstract
In the current study, we present the development of the Global Self-Esteem (GSE) measure. The six-item GSE fulfills a need for a short unidimensional measure of global self-esteem conceptualized as “overall positive view of self.” The construct is traditionally measured by the Rosenberg Self-Esteem Scale (RSE); however, several important shortcomings of the scale have been highlighted in the recent research. To improve the operationalization of global self-esteem, the shortcomings of the RSE and of the other measures intended to measure the construct are addressed in the construction of the GSE. Initial psychometric characteristics of the GSE, obtained in a pilot study, are reported. The results of exploratory factor analysis indicated unidimensionality of the measure—a single factor accounted for 78% of the variance in the GSE items, and the magnitude of factor loadings ranged from .81 to .91. Internal consistency reliability was high (ordinal α = .95), and expected relations between the GSE scores and other self-esteem measures were found. The utility of the measure and goals for future research are discussed in the context of limitations of the current study.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".