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Record W2418927485 · doi:10.5038/1911-9933.10.1.1279

In the Land of the Mountain Gods: Ethnotrauma and Exile among the Apaches of the American Southwest

2016· article· en· W2418927485 on OpenAlexvenueno aff
M. Hunt Watkinson

Bibliographic record

VenueGenocide Studies and Prevention · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousPersecutionImprisonmentEthnic groupEthnologyHistoryIdentity (music)Gender studiesSociologyGeographyAnthropologyCriminologyPolitical scienceArtLawAesthetics

Abstract

fetched live from OpenAlex

In the mid to late nineteenth century, two Indigenous groups of New Mexico territory, the Mescalero and the Chiricahua Apaches, faced violence, imprisonment, and exile. During a century of settler influx, territorial changeovers, vigilante violence, and Indian removal, these two cousin tribes withstood an experience beyond individual pain best described as ethnotrauma. Rooted in racial persecution and mass violence, this ethnotrauma possessed layers of traumatic reaction that not only revolved around their ethnicity, but around their relationship with their home lands as well. Disconnected from the ritual resources and sacred geographies that made up every day Apache living, both groups faced a profound and uphill struggle to maintain their community and very identity in the wake of immense and collective psychological distress. This essay emphasizes the role that geography plays in both the immediate impact of exile trauma and in the healing possibilities that this sacred connection to place has to offer Indigenous communities, even in the midst of exile.

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: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.009
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.336
Teacher spread0.305 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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