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Record W3168973356 · doi:10.3138/9781487513764-012

11 Is There a Role for Anthropology in Cultural Reproduction? Maps, Mining, and the “Cultural Future” in Central Australia

2017· book-chapter· en· W3168973356 on OpenAlexaboutno aff
Nicolas Peterson

Bibliographic record

VenueUniversity of Toronto Press eBooks · 2017
Typebook-chapter
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsReproductionAnthropologyCultural anthropologyGeographyEcological anthropologySociologyHistoryEcologyBiologyArt historyAnthropology of artPerformance art

Abstract

fetched live from OpenAlex

Entangled Territorialities offers vivid ethnographic examples of how Indigenous lands in Australia and Canada are tangled with governments, industries, and mainstream society. Most of the entangled lands to which Indigenous peoples are connected have been physically transformed and their ecological balance destroyed. Each chapter in this volume refers to specific circumstances in which Indigenous peoples have become intertwined with non-Aboriginal institutions and projects including the construction of hydroelectric dams and open mining pits. Long after the agents of resource extraction have abandoned these lands to their fate, Indigenous peoples will continue to claim ancestral ties and responsibilities that cannot be understood by agents of capitalism. The editors and contributors to this volume develop an anthropology of entanglement to further examine the larger debates about the vexed relationships between settlers and indigenous peoples over the meaning, knowledge, and management of traditionally-owned lands.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.114
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.018
Scholarly communication0.0070.003
Open science0.0010.003
Research integrity0.0010.002
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 head0.053
GPT teacher head0.334
Teacher spread0.281 · 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 designQualitative
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

Citations12
Published2017
Admission routes1
Has abstractyes

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