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Record W1882158961 · doi:10.3968/7690

The Construction of the Legal Environment of the Transformation of the Scientific and Technological Achievements in China

2015· article· en· W1882158961 on OpenAlexvenueno aff
Jie Qin, Song Wei

Bibliographic record

VenueCanadian social science · 2015
Typearticle
Languageen
FieldDecision Sciences
TopicResearch, Science, and Academia
Canadian institutionsnot available
Fundersnot available
KeywordsChinaGovernment (linguistics)Technological changeLegislationNormativeState (computer science)Mechanism (biology)BusinessLaw and economicsPolitical scienceLawEconomicsComputer science

Abstract

fetched live from OpenAlex

The transformation of scientific and technological achievements is a very important way that combines economy with science and technology. A good legal environment can push the transformation of scientific and technological achievements. Based on the normative analysis of the relevant laws issued by the National People’s Congress or State Council, it is found that there are some problems in the legal system of the transformation of scientific and technological achievements in China The law of promoting the transformation of scientific and technological achievements is too lagged and inflexible; the governmental functions in the transformation of scientific and technological achievements are not clear; The legal protection mechanism on the funds of the transformation of scientific and technological achievements is not perfect; The legal system of scientific and technological intermediary services is not good enough. Through the content analysis, we put forward several suggestions. Amending the law of promoting the transformation of scientific and technological achievements and enhancing the operability of the law; protecting the government to give full play to its functions in the transformation of scientific and technological achievements through legislation; Improving the legal safeguard mechanism on the funds of the transformation of scientific and technological achievements; Clarify the relevant provisions of the scientific and technological intermediaries and improving the mechanism of legal supervision.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.993
Threshold uncertainty score0.321

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.004
Science and technology studies0.0070.007
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.051
GPT teacher head0.324
Teacher spread0.272 · 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 designTheoretical or conceptual
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

Citations1
Published2015
Admission routes1
Has abstractyes

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