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Record W7095317226

MASTER

2016· article· en· W7095317226 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsExhibitionCentennialState (computer science)Government (linguistics)George (robot)Power (physics)NarrativeNationalism
DOInot available

Abstract

fetched live from OpenAlex

reproduced in whole or in part, by photocopy or other means, without the permission of the author. Drawing upon field work, mass media accounts, and Canadian government internal documents, this thesis considers how settler/Aboriginal power relations were reproduced when Taiwan Aboriginal artefacts held by the Royal Ontario Museum were used in a 2001 exhibition in Taipei to commemorate the centennial of the death of the Taiwanese nationalist hero, George Leslie Mackay (1 844-1 901). I argue that this exhibition and related Taiwan-Canada state Aboriginal exchanges have been hierarchically structured by organizational narratives in which coalitions of settler state institutions function as adept heroes who quest to help inept Aboriginal peoples deal with various reified difficulties such as "cultural loss " or "economic development. " Aboriginal participants are portrayed as thankful for the heroes ' sacrifices and thereby morally validate the heroes ' quests and relations between settlers and Aborigines. Helping Aborigines thereby allows for moral claims by involved institutions that just @ the use of Aboriginal exchanges to advance

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.220
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.7800.602

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 head0.030
GPT teacher head0.196
Teacher spread0.167 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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