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Record W2604510702

An International Examination of Educational Equity and Opportunity using a Reciprocal Learning Lens

2017· article· en· W2604510702 on OpenAlexaffabout
Cheryl J. Craig, Michael Connelly, Shijing Xu, Yuhua Bu, Yishin Khoo, Dan Tan, Shijian Chen, Ying Li, Lynn Paine

Bibliographic record

Venue2017 Conference of the Canadian Society for the Study of Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsUniversity of WindsorUniversity of Toronto
Fundersnot available
KeywordsReciprocalEquity (law)Public relationsPolitical scienceCross-culturalSociologyPedagogy
DOInot available

Abstract

fetched live from OpenAlex

This international symposium examines equity and opportunity in a Social Sciences and Humanities Research Council of Canada cross-cultural Canada-China educational study. The ideas of cross-cultural reciprocal learning and educational partnerships govern the work. The project involves a research-development infrastructure consisting of a cross-cultural sister school network and a preservice teacher education exchange program. Knowledge mobilization is a priority for three “knowledge to action” audiences: academic, professional, and public. Equity and opportunity are shown as a function of place and cultural interaction and are made visible through diverse, reciprocal learning partnerships spotlighted in this session. This cross-cultural, reciprocal work stands to transform transnational studies and how intercultural exchanges take place. Audience members will learn how reciprocal learning can be globally cultivated.

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)0.009
metaresearch head score (Gemma)0.008
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: none
Teacher disagreement score0.026
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0140.038
Scholarly communication0.0180.013
Open science0.0010.014
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.000

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 head0.219
GPT teacher head0.438
Teacher spread0.219 · 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
Published2017
Admission routes2
Has abstractyes

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