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Record W2370513143

Analysis on Competition of Social Science in Gansu Province——From the Visual Angle of the Projects Supported by the National Social Science Fund

2015· article· en· W2370513143 on OpenAlexaff
Wang Xiao-l

Bibliographic record

VenueTechnology and Innovation Management · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicForest, Soil, and Plant Ecology in China
Canadian institutionsScience North
Fundersnot available
KeywordsCompetition (biology)Unit (ring theory)Distribution (mathematics)ProductivityPlan (archaeology)Political scienceRegional scienceBusinessEconomic growthSociologyEconomicsGeographyPsychologyEcology
DOInot available

Abstract

fetched live from OpenAlex

The project approval of National Social Science Fund has become the key indicator in assessing the competitiveness of a unit in philosophy and social science studies. Based on multi-angle analysis of the number of National Social Science Fund Project,unit distribution,discipline structure and core person responsible in 9th Five-Year plan of Gansu province,the paper described the research productivity distribution and variation of the philosophy and Social Science during the eighteen years of Gansu province. Furthermore,it put forward to strengthen the integration of resources and cultivates young academic leading figures,and enhance competitive advantage of project and strengthens the developing potential of the researches,which is essential for raising the number of National Social Science Fund Project of Gansu province and improving the competition of Philosophy and social science research.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.995
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.038
GPT teacher head0.334
Teacher spread0.295 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

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

Citations0
Published2015
Admission routes1
Has abstractyes

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