Globalisation and Labour Productivity in the Malaysian Manufacturing Sector
Bibliographic record
Abstract
Globalisation process has forced the Malaysian manufacturing sector to strengthen its ability to compete in the international market. Globalisation, coupled with advancement in information, communication and technology has increased the demand for quality labour, having knowledge and competing to maximise production. The objective of this paper is to analyse the depth of globalisation impact on labour productivity in the Malaysian manufacturing sector. The analysis has used data from the Manufacturing Industrial Survey, Department of Statistics Malaysia comprising 24 years, from 1985 to 2008 and selected six sub-industries. A multiple regression model using panel data is estimated to analyse the relationship between labour productivity using capital-labour ratio, number of labour, foreign direct investment (FDI), foreign labour, economic openness and technology. Findings of the study show that globalisation indicators like FDI and economic openness have negative and significant effect on labour productivity in the manufacturing sector. The dummy period after the year 1995 is positive and significant reflecting that the impact of globalisation on labour productivity in the Malaysian manufacturing sector is higher after the year 1995 as compared to the years prior to 1995.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".