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Record W2386715724

The Argument on The General Education and Special Education in Social Work Field of China

2007· article· en· W2386715724 on OpenAlexaff
Liu Ying

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsScience North
Fundersnot available
KeywordsChinaArgument (complex analysis)Field (mathematics)Social workSociologyMetaphorEconomic shortageWork (physics)Social positionFace (sociological concept)Position (finance)Education policyHigher educationPolitical scienceSocial scienceSocial relationLawMedicineEngineeringEconomicsMathematics
DOInot available

Abstract

What Chinese social work education walks differs from western development path,this characteristic makes the social work education to face two kinds of choices by all means:general education or special education.Special education which metaphor a clear occupation position,can promote ability and personal legal right of social worker in the meantime,its shortage of place is imperfection of the whole angle of view in general education.

Stored with the screening record, where it is evidence for the labels above.

How this classification was reachedexpand

The three-model screen

all 5,600 screened works →

All three models called this out of scope.

stratum: aff_core · design weight: 5595.24 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: conceptual
about Canada: no
confidence: medium

Argument about general versus specialized professional education in Chinese social work; concerns vocational training, not the research workforce.

GPT-5.6 (high)OUT
genre: conceptual
about Canada: no
confidence: high

The work debates general and specialized social-work education rather than research itself.

Grok 4.5OUT
genre: conceptual
about Canada: no
confidence: high

Debate on general vs specialized social-work professional education in China, not scientific research workforce.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.069
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0050.011
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0070.000

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 head0.022
GPT teacher head0.389
Teacher spread0.367 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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
Published2007
Admission routes1
Has abstractyes

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