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Record W2235864645 · doi:10.2991/msetasse-15.2015.129

Comparative Study on Chinese and Canadian Education Policies for Trans-culture Immigrants

2015· article· en· W2235864645 on OpenAlexaboutno aff
Changxing Zhao, Ruiqin Duan, Jie Zhang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicChina's Ethnic Minorities and Relations
Canadian institutionsnot available
FundersFundamental Research Funds for the Central Universities
KeywordsProsperityHarmony (color)ChinaImmigrationOpenness to experienceSocial harmonyPolitical scienceEconomic growthInequalityConnotationDevelopment economicsSociologyEconomicsSocial sciencePsychology

Abstract

fetched live from OpenAlex

The implementation of multi-cultural education promotes the prosperity and sustainable development of Canada; however the racial inequality is yet eliminated thoroughly.Under the mechanism of reversed pressure, China sets out to response to the education for migrant children, from passive to initiative, from restriction to openness, from difference to equality, from administration to service, keep improving policy level and right guarantee level.From an overall perspective of two countries' education policies for immigrants, they are highly consistent in maintain national stability, social harmony and racial equality, however, there is significance difference in the background, connotation, path and so on of polices due to the difference on historic culture and realistic national condition.China should rationally take Canada as a reference based on its actual situation.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.946
Threshold uncertainty score0.394

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0060.001
Scholarly communication0.0020.001
Open science0.0010.001
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 head0.064
GPT teacher head0.404
Teacher spread0.340 · 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 designQualitative
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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