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Record W3088837065 · doi:10.4000/abe.8106

Imperial Atmospheres: Race and Climate Control on the Niger

2020· article· en· W3088837065 on OpenAlexaff
Dustin Valen

Bibliographic record

VenueABE Journal · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Maritime and Colonial Histories
Canadian institutionsConcordia University
Fundersnot available
KeywordsGlobeParadiseCivilizationRace (biology)Environmental ethicsHistoryPolitical scienceGeographySociologyArchaeologyGender studies

Abstract

fetched live from OpenAlex

This essay explores how nineteenth-century environmental technologies rendered climates mobile through an examination of a British-led mission to the Niger River in West Africa in 1841. To protect white sailors from the tropical African climate, expedition authorities invited Scottish ventilation engineer David Boswell Reid to consult on the design of three iron steam ships. Using a centralized air intake connected to a wind sail, Reid created a pressurized plenum below deck whose air he medicated by treating it with chemicals. The Niger mission exemplifies how Victorian ventilating practices were informed by unilineal theories of progress in which climate served as a key index for measuring animal, vegetable, and human progress. Regions of the globe with climates similar to Britain’s were considered ideal for colonization. Tropical climates, however, were thought to have damaging effects on European bodies. Climate was also blamed for impeding the rise of civilization. Drawing on medical journals and reports, this essay discusses nineteenth-century ventilating practices in terms of their relationship to the tropical anxieties of their time. It posits climate control as an ecological mission within the broader project of British imperialism, and shows how Western ideas about thermal comfort emerged through a discursive entanglement with racial anthropology and imperial interests in the torrid zone.

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)0.001
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 score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.014
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.252
Teacher spread0.241 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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