Review of: "Effect of Organisational Factors on Intrapreneurial Behaviour of Public University Academicians in Malaysia"
Bibliographic record
Abstract
Potential competing interests: No potential competing interests to declare.The idea presented in this paper is intriguing and warrants further investigation.The text provides a summary and body that cover the main points of the study.However, there are areas that require correction and clarification.Firstly, in the summary, the authors mention gender as a mediating variable, while in the analysis and body of the text, they refer to the moderating effect of gender.This inconsistency should be addressed in the manuscript.The authors should also correct this error in the recommendations for future researchers.The authors mention that the study is based on primary and secondary data, but they do not specify the purpose and details of each data source used.The authors do not provide information on the inclusion and exclusion criteria used in selecting their sample.While they mention that they targeted academics working in public universities, it is unclear whether administrators, doctoral students who work in and for the universities and receive a salary, deans, and heads of departments were included or excluded.The authors do not mention the year and period in which they collected the data.The authors do not explain how they operationalized their variables and the measurement scales used.How was the intrapreneurial behavior of academics measured?And how were the independent variables measured?The items used for each latent variable should be provided.Additionally, references should be cited for the pre-existing scales used.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".