MétaCan
Menu
Back to cohort

An Empirical Study on Campus Dwelling Environment Quality in Beijing and Its Influencing Factors

2012· article· en· W1787616313 on OpenAlexvenueno aff
Zhang Gui-fang, Yanjie Ning, Luqing Fan, Chuhan Mei, Lijie Tian, Ziqi Chu

Bibliographic record

VenueStudies in sociology of science · 2012
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsBeijingNatural (archaeology)Cultural environmentQuality (philosophy)Environmental qualityConstruct (python library)PopulationNatural landscapeEnvironmental resource managementChinaGeographyBusinessArchitectural engineeringEcologySociologySocial environmentEnvironmental scienceEngineeringComputer scienceSocial science

Abstract

fetched live from OpenAlex

Combining with the current dwelling environmental assessment system, this article reviews the domestic and foreign theoretical documents, and tries to construct an evaluation model based on the influencing factors of campus dwelling environment quality in Beijing, including natural landscape, amenities and cultural environment. The research indicates that the campus dwelling environment quality is linearly related with and can be effectively predicted by these three factors. It also shows that the regression coefficient of cultural environment is the highest among the three; but most interviewees didn’t appraise their campus dwelling environment quality high. Therefore, colleges in Beijing need to improve especially in the following three aspects – gas power system (natural landscape), population density (amenities) and manager quality (cultural environment) – to make the campus dwelling environment clean pleasant and eco-friendly. Key words : Universities in Beijing; Dwelling environment; Natural landscape; Amenities; Cultural environment

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.088
GPT teacher head0.410
Teacher spread0.322 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueStudies in sociology of scienceSame topicSustainable Building Design and AssessmentFrench-language works237,207