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Record W2751788751

Constructing School Science: Physics, Biology, and Chemistry Education in Ontario High Schools, 1880 -1940

2014· dissertation· en· W2751788751 on OpenAlexaboutno aff
Michelle D. Hoffman

Bibliographic record

VenueTSpace (University of Toronto) · 2014
Typedissertation
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationScience educationEngineering physicsPhysicsPsychology
DOInot available

Abstract

fetched live from OpenAlex

This thesis is a history of science education reform in Ontario, from 1880 to 1940. It examines successive eras of science education reform in secondary (pre-university) schools, including the rise of laboratory science; the spread of general science programs; and efforts to teach science “humanistically.” This research considers the rhetorical strategies employed by scientists and educators to persuade educational policymakers and the public about the value and purpose of science education. Their efforts hinged in large part on building a moral framework for school science, which they promoted an essential stimulus to students’ mental development and a check on the emotive influence of literature and the arts. These developments are placed in international context by examining how educational movements conceived in other places, especially the United States and Britain, were filtered and transformed in the distinct educational context of Ontario. Finally, the sometimes-blurry boundaries between “academic” science education and technical education are explored, most notably in Ontario in the late nineteenth century, when science education was undergoing a rapid, driven expansion in the province’s high schools. This research contributes to a relatively recent body of literature that promotes a greater appreciation of pre-college science education – an area that has often been overlooked in favour of higher education and the training of specialists – as an important window onto the public perception of science.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.974
Threshold uncertainty score0.859

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0260.013
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.002
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 head0.006
GPT teacher head0.244
Teacher spread0.237 · 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.

Study designQualitative
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

Citations1
Published2014
Admission routes1
Has abstractyes

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