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Record W4378439683 · doi:10.1515/9780773598935

These Mysterious People, Second Edition

2016· book· en· W4378439683 on OpenAlexaboutno aff
Susan Roy

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2016
Typebook
Languageen
FieldSocial Sciences
TopicHistorical and Cultural Archaeology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHistoryComputer science

Abstract

fetched live from OpenAlex

Archaeologists studying human remains and burial sites of North America’s Indigenous peoples have discovered more than information about the beliefs and practices of cultures - they have also found controversy. These Mysterious People shows how Western ideas and attitudes about Indigenous peoples have transformed one culture’s ancestors, burial grounds, and possessions into another culture’s "specimens," "archaeological sites," and "ethnographic artifacts," in the process disassociating Natives from their own histories. Focusing on the Musqueam people and a contentious archaeological site in Vancouver, These Mysterious People details the relationship between the Musqueam and researchers from the late-nineteenth century to the present. Susan Roy traces the historical development of competing understandings of the past and reveals how the Musqueam First Nation used information derived from archaeological finds to assist the larger recognition of territorial rights. She also details the ways in which Musqueam legal and cultural expressions of their own history - such as land claim submissions, petitions, cultural displays, and testimonies - have challenged public accounts of Aboriginal occupation and helped to define Aboriginal rights in Canada An important and engaging examination of methods of historical representation, These Mysterious People analyzes the ways historical evidence, material culture, and places themselves have acquired legal and community authority.

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)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.022
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0040.005
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0220.008

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 head0.015
GPT teacher head0.218
Teacher spread0.203 · 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
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

Citations3
Published2016
Admission routes1
Has abstractyes

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