Analysing the Validity of Union Commitment Scale Using Confirmatory Factor Analysis with Malaysian Samples
Bibliographic record
Abstract
This study was carried out to confirm the validity of the union commitment scale proposed by Bayazit in measuring union commitment among union officials. Union commitment was represented using three sub-constructs namely loyalty towards union (12 items), willingness to work for the union (4 items) and responsibility towards union (4 items). The scale was modified to cater for the respondents consisting of union officials and local environment. A total of 676 respondents’ namely union officials from the states of Selangor and Federal Territory (Putrajaya and Kuala Lumpur), Malaysia who were involved as the research subjects had been selected using stratified random sampling technique. Confirmatory factor analysis (CFA) was conducted using the AMOS software version 21. Initially, the measurement model of union commitment had demonstrated poor-fit indices whilst the correlation between sub-constructs was shown to be high. However, after undergoing the goodness-of-fit, results for the fit indices for measurement model were found to have been improved. The evaluation on the validity and reliability has also been performed for the measurement model. The number of items remaining for modified measurement model was 13, with 7 items for loyalty towards union, 2 items for the willingness to work for the union and 4 items for responsibility towards the union. Therefore, this scale which had undergone the CFA process is valid as the measurement tool to assess the level of commitment among union officials.
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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 | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".