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Record W2561398806 · doi:10.11647/obp.0103

Open Education

2016· book· en· W2561398806 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueOpen Book Publishers · 2016
Typebook
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsnot available
FundersDefense Language Institute Foreign Language CenterSchool of Liberal ArtsUniversity of British ColumbiaUniversity of Southern QueenslandUniversity of TasmaniaJoint Information Systems CommitteeHigher Education AcademyUniversity of EdinburghUniversity of PittsburghWilliam and Flora Hewlett Foundation
KeywordsOpen educationPolitical sciencePedagogyMathematics educationSociologyPsychology

Abstract

fetched live from OpenAlex

This insightful collection of essays explores the ways in which open education can democratise access to education for all. It is a rich resource that offers both research and case studies to relate the application of open technologies and approaches in education settings around the world. Global in perspective, this book argues strongly for the value of open education in both the developed and developing worlds. Through a mixture of theoretical and practical approaches, it demonstrates that open education promotes ideals of inclusion, diversity, and social justice to achieve the vision of education as a fundamental human right. A must-read for practitioners, policy-makers, scholars and students in the field of education.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesScholarly communication, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.280
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0350.026
Open science0.0190.008
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.005

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 head0.299
Teacher spread0.275 · 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