Psychological empowerment in the South African military: The generalisability of Menon's Scale
Bibliographic record
Abstract
The aim of this study was to investigate the factorial validity and internal consistency of the Menon Scale for Psychological Empowerment, developed in the United States and Canada and tested in Australia and Greece, in the South African National Defence Force (SANDF). The 2231 participants in the study represented the gender and racial distribution of the military population. The South African data initially yielded a two-factor structure. A forced three-factor structure rendered acceptable alpha coefficients, but did not resemble the theoretically expected factors. The forced factor analyses were repeated for Africans, Asians and Coloureds, and Whites separately. Results for the first two groups kept the original structure, whereas the factor structure for the white participants resembled the theoretically hypothesised factors. The forced three-factor structures rendered very high internal consistencies for the total scale, but one factor for both the African and the Asian and Coloured groups showed unsatisfactory reliability, suggesting a single underlying empowerment factor. This was confirmed by high correlations between subscales. Menon’s model seemingly fits the South African data slightly better for the white participants than for their non-white counterparts. The scale thus needs to be revised for the different cultural groups.
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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 | 0.023 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".