MétaCan
Menu
Back to cohort

A Four-Step Process to Reposition Small Schools as Sites Within Teaching and Learning Networks

2011· book-chapter· en· W2479908993 on OpenAlexaffabout
Ken Stevens

Bibliographic record

VenueAdvances in educational marketing, administration, and leadership book series · 2011
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsVocational educationProcess (computing)Mathematics educationRural areaSociologyPedagogyPolitical sciencePsychologyComputer science

Abstract

fetched live from OpenAlex

The international problem facing small high schools in rural communities of providing access to educational and vocational opportunities that approximate those available to urban students has been addressed by repositioning these institutions as sites within teaching and learning networks in the Canadian province of Newfoundland and Labrador. Four inter-connected dimensions of change are outlined (technological, pedagogical, organizational, and conceptual) whereby small rural schools in this Canadian province were repositioned as sites in teaching and learning networks thereby enhancing educational and vocational opportunities for senior students. There are implications in these changes for the professional education of high school teachers who are increasingly likely to be required to teach in networked classes as well as in traditional classrooms.

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)0.008
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.033
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0130.010
Scholarly communication0.0090.006
Open science0.0030.012
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0090.003

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 head0.045
GPT teacher head0.260
Teacher spread0.216 · 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 designNot applicable
Domainnot available
GenreMethods

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 routes2
Has abstractyes

Explore more

Same venueAdvances in educational marketing, administration, and leadership book seriesSame topicInnovative Approaches in Technology and Social DevelopmentFrench-language works237,207