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Record W248175483 · doi:10.4324/9781032659718-14

The Hard-Soft School *

2023· article· en· W248175483 on OpenAlexaboutno aff
Anthony Barton

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Education Studies and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationPsychologyComputer sciencePedagogy

Abstract

fetched live from OpenAlex

It appears that there was an information explosion in the realm of finance before the stock market crash of 1929. Now it seems that there is an information explosion in education. Pieces of paper are exchanging hands, but the exchange bears less and less resemblance to the real-life education of children, most of which now takes place outside the schools. A barred gate in a brick wall opens into an asphalt playground. A notice on the wall reads bicycle riding, handball playing, hardball playing, prohibited by the toronto board of education. A tangle of mud, trees, grass, and children’s constructions leads gradually into a covered, heated area. As the ground changes from mud to linoleum, a wooden grid appears low overhead. From this lattice of unfinished pine, many things are hanging: electronic sculptures, measuring instruments, polyethylene curtains, stage flats, mirrors, and microphones.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.114
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.006

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 head0.051
GPT teacher head0.353
Teacher spread0.302 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2023
Admission routes1
Has abstractyes

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