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Record W1931082609 · doi:10.21971/p71010

Popular Darwinism and Geography Textbooks in Canada, 1850-1920

2008· article· en· W1931082609 on OpenAlexvenueaboutno aff
Eric Gormley

Bibliographic record

VenueCrossing boundaries · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Science and Natural History
Canadian institutionsnot available
FundersU.S. Geological SurveyColgate University
KeywordsDarwinismSign (mathematics)Mechanism (biology)Darwin (ADL)Race (biology)GeographyPopulationSocial scienceSociologyEpistemologyDemographyGender studiesPhilosophyMathematicsEngineering

Abstract

fetched live from OpenAlex

Influenced by Darwin's ideas, geographers in the late nineteenth century attempted to understand how the earth affected man. Disseminating their ideas through textbooks, geographers established what physical and climatic features were favourable for advancement and also defined what constituted progress or success. A dense population, for instance, was desirable, a sign the race was succeeding. This paper analyzes pre-and post-Darwinian geography textbooks used in the Canadian school system, indicating that they helped to shape culture at the turn of the century. Geography textbooks in Canadian schools were an important mechanism for the transmission of popular conceptions of Darwinian thought.

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)0.010
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score1.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0090.018
Science and technology studies0.0080.005
Scholarly communication0.0050.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.200
Teacher spread0.177 · 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

Citations2
Published2008
Admission routes2
Has abstractyes

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