The Theory of Planned Behaviour as a Framework for Whistle-Blowing Intentions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p>This study adopts the Theory of Planned Behaviour as an underlying model to investigate its relevance, by examining the link between attitude, subjective norm and perceived behavioural control to account for whistle-blowing intentions. The data were analysed using a structural equation modelling (SEM) technique with the use of Partial Least Square approach (PLS). Using a sample of 262 Malaysian police officers, the analysis showed that TPB provides a sound framework for predicting both internal and external whistle-blowing intentions. Additionally, both internal and external whistle-blowing intentions are significantly influenced by attitude. Subjective norm is found to positively influence internal whistle-blowing intentions, while perceived behavioural control positively influences external whistle-blowing intentions. Hence, it is hoped that the results of this study will be a useful source of information to law makers, policy makers, institutions, management and the like in supporting whistle-blowing practices and thus enhancing accountability and strengthening good corporate governance in work places.</p>
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.083 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it