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Record W2035603363 · doi:10.1353/scp.0.0073

The International Publication Productivity of Malaysia in Social Sciences: Developing a Scientific Power Index

2009· article· en· W2035603363 on OpenAlexvenueno aff
M R Davarpanah

Bibliographic record

VenueJournal of Scholarly Publishing · 2009
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsnot available
Fundersnot available
KeywordsCitation indexIndex (typography)Social Sciences Citation IndexProductivityScience Citation IndexImpact factorSocial scienceCitationPower (physics)Political scienceSociologyRegional scienceEconomicsEconomic growthComputer scienceLaw

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.163
metaresearch head score (Gemma)0.254
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Scholarly communication, Open science
Consensus categoriesMetaresearch, Bibliometrics, Scholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1630.254
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0450.131
Science and technology studies0.0010.000
Scholarly communication0.1650.080
Open science0.0070.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.464
GPT teacher head0.522
Teacher spread0.058 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2009
Admission routes1
Has abstractyes

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