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Record W2351197262 · doi:10.18192/olbiwp.v3i0.1090

Introduction to Part 1

2011· article· en· W2351197262 on OpenAlexaffvenueabout
Stacy Churchill, Monika Jezak, Sylvie A. Lamoureux

Bibliographic record

VenueOLBI Journal · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsUniversity of OttawaUniversity of Toronto
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

This volume presents the results of two separate seminars organized by researchers at the Official Languages and Bilingualism Institute, University of Ottawa, around the topic of language policy. 1 Part 1 deals with the interaction between public policies, policy-making processes, and outcomes with respect to the role of literacy in the integration of immigrants to Canada.In other words, Part 1 is a broad case study of research into language policy.Part 2 consists of selected papers from an invitational seminar held at the University of Ottawa with early career researchers to discuss the new contours of language policy studies.The over-arching objective of the two parts is to examine how language policy is now being researched within broader frameworks than those usually adopted by most media coverage and Canadian academic writing, all of which gravitate toward discussion of governmental intervention and regulation.The readers of the volume will immediately note that the traditional Canadian focus on bilingualism involving two languages -English and Frenchis far too narrow to encompass the whole.The inadequacy of the old focus reflects both demographic changes in Canadian society and a growing awakening to the reality of what Europeans now call plurilingualism.In spite of academic 1 The seminar on Language Policy and Adult Immigrant Literacy at the annual meeting of the Canadian Association od Applied

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.387
Threshold uncertainty score0.875

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0040.001
Scholarly communication0.0050.003
Open science0.0020.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.3870.197

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 head0.142
GPT teacher head0.459
Teacher spread0.317 · 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.

Study designNot applicable
Domainnot available
GenreEditorial

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
Published2011
Admission routes3
Has abstractyes

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