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Record W205112898

Moving Science Classes to the Community: A Question of Social Justice.

2007· article· en· W205112898 on OpenAlexaboutno aff
Wolff‐Michael Roth

Bibliographic record

VenueEducation Canada · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNumeracyScientific literacySubject (documents)Subject matterLiteracyScience educationSocial science educationPolitical scienceEconomic JusticePedagogySocial justiceSociologyPublic relationsMathematics educationSocial sciencePsychologyCurriculumLibrary science
DOInot available

Abstract

fetched live from OpenAlex

Research Council of Canada launched a pilot program, Centres for Research in Youth, Science Teaching and Learning, to provide a forum for those individuals and organizations interested in developing and enhancing the skills of, and the resources available to, science and mathematics teachers. It attempts to address a decades-old, recurrent problem: Despite the tremendous efforts that have gone into improving the teaching of science since the 1960s, in Canada and around the world, there continues to be a dearth of students who enrol in science-related careers. Many educators and policy makers argue that science literacy and numeracy are vital skills for successfully participating in the economy of this century. But how do we increase the levels of scientific literacy, let alone make science a subject for all students, when the subject matter itself has been keeping students away?

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)0.020
metaresearch head score (Gemma)0.044
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 score0.147
Threshold uncertainty score0.380

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.044
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0670.049
Scholarly communication0.0190.014
Open science0.0050.018
Research integrity0.0200.025
Insufficient payload (model declined to judge)0.0140.001

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 head0.037
GPT teacher head0.307
Teacher spread0.270 · 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

Citations1
Published2007
Admission routes1
Has abstractyes

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