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Record W7132976238

A critique of language and literacy in educational policy: Hawaii and Canada

2002· dissertation· W7132976238 on OpenAlexaboutno aff
Rhonda Leigh Paulsen

Bibliographic record

VenueTSpace · 2002
Typedissertation
Language
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsMulticulturalismCurriculumInclusion (mineral)LiteracyField (mathematics)Language policyCurriculum developmentPoliticsEducational research
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this research is to provide a critical analysis of educational policy in both Hawaii and Canada. Policy development requires an understanding of social, political and historical issues of language and current curriculum development. This research gives institutional policy makers a lens through which to view educational policy and a more comprehensive framework to identify areas that require consideration and revision. This research is important as it identifies the need for change in policy development and makes recommendations in areas of instruction, evaluation, and cultural and linguistic inclusion in the curriculum. The analysis shows that current policy, particularly with regard to language, is not meeting the needs of a multicultural and multilingual society. The outcome of the research also indicates that there is more evidence needed to support multilingual education, and therefore this is an area from which the field can benefit from further research.

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)0.007
metaresearch head score (Gemma)0.023
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 score0.135
Threshold uncertainty score0.978

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0230.021
Scholarly communication0.0130.005
Open science0.0030.006
Research integrity0.0070.010
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 head0.482
Teacher spread0.460 · 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
Published2002
Admission routes1
Has abstractyes

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