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Record W2014042933 · doi:10.1177/096746080000700401

On the Colonial Genealogy of George Vancouver’s Chart of the North-West Coast of North America

2000· article· en· W2014042933 on OpenAlexaboutno aff
Daniel Clayton

Bibliographic record

VenueEcumene · 2000
Typearticle
Languageen
FieldArts and Humanities
TopicMaritime and Coastal Archaeology
Canadian institutionsnot available
Fundersnot available
KeywordsColonialismGeorge (robot)Power (physics)GeographyVariety (cybernetics)HistoryWest coastArchaeologyGenealogyEthnologyCartographyArt historyOceanographyGeology

Abstract

fetched live from OpenAlex

This paper contributes to the burgeoning critical literature on the history of cartography by tracking the links between maps, knowledge and power that stemmed from George Vancouver’s survey of the north-west coast of North America. Dispatched to the region by the British in 1791, Vancouver conducted an exhaustive cartographic survey and has been represented as the ‘true discoverer’ of the coast. It is argued here that he created a cartographic space (rather than simply discovered a pre-existing geography), and that his reconnaissance induced and supported a range of imperial and colonial practices. Vancouver’s work played a central role in the creation of a system of imperial inscription that primed the coast for colonial intervention. Attention is paid to the ways in which Vancouver’s project became (and remains) authoritative and influential in imperial and colonial terms: how it turned the coast into an arena of British imperial interest by occluding prior and alternative inscriptions on the land; how a variety of colonial images, projects and associations were derived from his work; and how we might now see his work in relation to the present.

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)0.000
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.167
Threshold uncertainty score0.337

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0140.010
Scholarly communication0.0050.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.010
GPT teacher head0.184
Teacher spread0.174 · 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

Citations16
Published2000
Admission routes1
Has abstractyes

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