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Record W2516389485 · doi:10.1108/ijem-11-2015-0151

School autonomy and 21st century learning: the Canadian context

2016· article· en· W2516389485 on OpenAlexaffabout
Paul Newton, José Da Costa

Bibliographic record

VenueInternational Journal of Educational Management · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsUniversity of AlbertaUniversity of Saskatchewan
Fundersnot available
KeywordsAutonomyOriginalityConstruct (python library)Context (archaeology)Learner autonomyValue (mathematics)SociologyPedagogyPolitical sciencePublic administrationPublic relationsSocial scienceLawQualitative researchGeographyComputer science

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to report on the policy and practice contexts for school autonomy and twenty-first century learning in Canadian provinces. Design/methodology/approach This paper reports on an analysis of policies in Canadian provinces (particularly the provinces of Alberta and Saskatchewan). The authors review policies related to school autonomy and twenty-first century learning initiatives. Findings In this paper, the authors argue that autonomy is a complicated and multi-levelled phenomena with a measure of autonomy devolved from the state to local school divisions, and yet other elements of autonomy devolved to the school and to individual teachers. The link between autonomy and twenty-first century learning are unclear as yet. This paper attempts to establish the policy contexts for school autonomy and twenty-first century learning without making claims about a causal relation between the two. Originality/value The originality of this paper lies in its description of autonomy beyond the school level. Autonomy, as a construct, is rarely examined as a dynamic process among multiple layers of the educational system.

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)0.003
metaresearch head score (Gemma)0.007
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: Empirical
Teacher disagreement score0.767
Threshold uncertainty score0.890

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.009
Science and technology studies0.0190.013
Scholarly communication0.0070.002
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.024
GPT teacher head0.327
Teacher spread0.304 · 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

Citations13
Published2016
Admission routes2
Has abstractyes

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Same venueInternational Journal of Educational ManagementSame topicParental Involvement in EducationFrench-language works237,207