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Record W6884610050 · doi:10.11575/jet.v8i2.43627

Reform as Social Tracking: The Case of Industrial Education in Ontario 1870-1900

2018· article· en· W6884610050 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Calgary · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsCompulsory educationInterpretation (philosophy)Industrial educationSocial changeSocial reformReform movementIndustrial RevolutionIdeal (ethics)Education economics

Abstract

fetched live from OpenAlex

The industrial education movement in Canada has been assessed by historians in two ways: as the educational expression of the Dominion's national development policy, and as an important step closer to the egalitarian ideal of universal, state-supported compulsory schooling.' Each interpretation marries industrial education to cherished social values: for the former, economic growth and the latter, equality of opportunity. The present study, based on an analysis of the group support and social functions associated with attempts to introduce various forms of industrial education, poses a counter-argument: that industrial education programs surfaced as one facet of an urban-centered, conservative, social reform movement which encompassed, as one of its vital concerns, the establishment of controls over the character, behavior and occupational future of poor and delinquent children.2 As such, industrial education was more a bane, than a boon, to the working class.

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)0.001
metaresearch head score (Gemma)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.780
Threshold uncertainty score0.905

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0330.014
Scholarly communication0.0050.001
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.026
GPT teacher head0.235
Teacher spread0.209 · 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
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

Citations0
Published2018
Admission routes1
Has abstractyes

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