The International Publication Productivity of Malaysia in Social Sciences
Bibliographic record
Abstract
The purpose of this study is to evaluate publication output and citation impact in the social sciences in Malaysia, based on Social Science Citation Index (SSCI) data, for the period 1999–2008. In addition to the analysis of trends in publication and citation patterns and national publication profiles, an attempt is made to explore the strengths and weakness of different fields, using a new mathematical index, the scientific power index (PI). The findings indicate that publication output in the social sciences has been on the increase since 1999. Mostpapers have been published in median-impact-factor journals (mean impact factor of 2.72 per paper). Internationally co-authored publications represented 77 per cent of all citations. Most of the prolific authors are from the highly productive institutions; however, none of highly cited first authors are from highly productive institutions. Psychology, economics, management, and environmental studies are the dominant fields in Malaysian social sciences.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.013 | 0.022 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".