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Record W4402110063 · doi:10.55016/ojs/jet.v16i1.43917

Wasted Resources: What Educational Philosophers Might Contribute to Educational Theory But Often Don't

2018· article· en· W4402110063 on OpenAlexaff
Brian Hendley

Bibliographic record

VenueJournal of educational thought. · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsEducation theoryEducational resourcesEpistemologySociologyMathematics educationEngineering ethicsPedagogyPsychologyPhilosophyPolitical scienceEngineeringHigher education

Abstract

fetched live from OpenAlex

According to T. W. Moore (Educational Theory: An Introduction, London, 1974), general theories of education of the sort developed by philosophers from Plato to Dewey have quite rightly gone out of fashion. Moore would restrict the contemporary philosopher to a more formal, analytical contribution to educational theory. The author contends that he (and many of his fellow philosophers of education) ignores the special resources a philosopher can bring to educational questions as an educated man, coming from a distinguished tradition of analysis and synthesis, and usually engaged in teaching. These are resources that the current educational system can afford to waste.

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)0.026
metaresearch head score (Gemma)0.043
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.026
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.043
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.005
Science and technology studies0.0120.096
Scholarly communication0.0260.063
Open science0.0040.016
Research integrity0.0120.016
Insufficient payload (model declined to judge)0.0100.003

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 head0.027
GPT teacher head0.351
Teacher spread0.324 · 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
GenreCommentary

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
Published2018
Admission routes1
Has abstractyes

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