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Record W2317474579 · doi:10.1386/eme.12.1-2.83_1

Eighteenth-century mapping of Cape Breton Island

2013· article· en· W2317474579 on OpenAlexaff
Erna MacLeod

Bibliographic record

VenueExplorations in Media Ecology · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsCape Breton University
Fundersnot available
KeywordsCapeGeographyIdeologyArchipelagoHistoryCartographyCompetition (biology)EthnologyArchaeologyPoliticsPolitical scienceEcology

Abstract

fetched live from OpenAlex

Abstract This article examines historic changes occurring in Europe related to printing and cartography as they played out on Cape Breton Island during the eighteenth century. The research explores Cape Breton maps as one example of the reciprocal relationship between technologies, ideas and natural environments. The advent of print engendered a transformation in human thought that elevated rational, scientific ways of knowing. Technology and ideology worked hand in hand to reshape the world through the use of increasingly accurate maps to explore and exploit new territory. The gradual shift from imaginative to increasingly accurate cartographic representations reveals the blending and balancing of artistic and scientific sensibilities in Europe and the New World. Advances in Europeans’ ability to more accurately map trade routes led to expanded knowledge about the world, particularly about peripheral regions with strategic or commercial potential. Cape Breton maps illustrate changes occurring in Europe and intimate the global consequences of those changes. Cape Breton’s geographic positioning and abundant cod stocks made the island important to both France and England. Cape Breton maps evolved through an exchange of ideas occurring in both Europe and the New World, particularly at Louisbourg because of its pivotal role as a centre for trade and military activity in the Anglo-French competition for control 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 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)0.002
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 score0.651
Threshold uncertainty score0.695

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.003
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.000

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 head0.028
GPT teacher head0.206
Teacher spread0.179 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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