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Record W2343962716 · doi:10.14288/1.0067517

Epistemological inequality : Aboriginal labor and knowledge in the geological surveys of George Mercer Dawson, 1874-1901

2009· article· en· W2343962716 on OpenAlexaffabout
Eva Jean Prkachin

Bibliographic record

VenuecIRcle (University of British Columbia) · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicAustralian Indigenous Culture and History
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGeorge (robot)InequalitySociologyEpistemologyPhilosophyHistoryArt historyMathematics

Abstract

fetched live from OpenAlex

Historical studies of Canadian science often ignore the assistance that Aboriginal people provided to frontier scientists. Monographs and biographies detailing the extraordinary career of Canadian geological surveyor George Mercer Dawson in the late nineteenth-century subsume the role that Aboriginal people played in his explorations. Postcolonial scholarship dealing with science criticizes the low epistemological status that scientific explorers accorded to Aboriginal knowledge, but neglects how collaboration between Aboriginal people and scientists influenced the knowledge that they produced in the New World. Dawson’s journals, technical notes, and scientific publications detail the numerous types of physical and intellectual labor that Aboriginal people contributed to his surveying expeditions in western Canada, particularly British Columbia, Alberta, and the Yukon. Using Aboriginal guides, general laborers, and informants enabled Dawson to cover substantial amounts of terrain during short surveying seasons, avoid hazards and delays, make ethnological observations, and record information on regions that he did not personally visit. Despite borrowing substantial amounts of knowledge from his Aboriginal guides and informants, Dawson did not equate Indigenous knowledge with scientific epistemologies. Dawson extracted the knowledge that Aboriginal people supplied him with from its epistemological packaging, but frequently acknowledged the Indigenous origin of his information, even in highly specialized scientific publications. Dawson’s work, then, serves as a powerful reminder of Aboriginal contributions to science produced during the exploration of North America.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.479
Threshold uncertainty score0.645

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.258
Teacher spread0.236 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2009
Admission routes2
Has abstractyes

Explore more

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