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Record W4392306872 · doi:10.1353/tech.2024.a920521

As Ceaseless as the Sea: How Modern Construction Machines Disrupted Canadian Senses and Sensibilities, 1870s–1940s

2024· article· en· W4392306872 on OpenAlexaboutno aff
Gilberto Fernandes

Bibliographic record

VenueTechnology and Culture · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsParallelsModernityPsycheHistory of technologySpectacleNoveltyAestheticsSociologyHistoryEngineeringPolitical scienceLawEpistemologyArchaeologyOperations managementArtPhilosophy

Abstract

fetched live from OpenAlex

Since the late nineteenth century, Canada has required modern construction machines for industrial growth. Thanks to their novelty and visibility, these machines entered the Canadian psyche, symbolizing hopes and fears about the relentless transformations of modernity. Metaphors depicting these machines as zoomorphic and monstruous reflected the environmental-technological infrastructures they built, which redefined nature through technologies like trains, ships, and automobiles. This article discusses how Anglo-Canadians, particularly Ontarians, interpreted technology, drawing parallels with the automobile's history. Both had a problematic coexistence with humans as equally empowering and oppressive mobile machines that were imposed on public spaces and constructed as necessary for progress. The builders used the machines' allure to present construction as an inclusive civic spectacle and foster public tolerance for their relentless disruptions. They accomplished this faster than the automobile industry came to dominate the streets, as evidenced by the celebration of "sidewalk superintendents," compared to the contentious reproach of "jaywalkers."

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)0.002
metaresearch head score (Gemma)0.004
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 score0.951
Threshold uncertainty score0.922

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0490.038
Scholarly communication0.0100.004
Open science0.0020.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.000

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 head0.004
GPT teacher head0.219
Teacher spread0.214 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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