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Record W4392525683 · doi:10.1353/cht.2023.a908123

About This Issue

2023· article· en· W4392525683 on OpenAlexaboutno aff
David J. Endres

Bibliographic record

VenueU.S. Catholic historian · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsComputational biologyComputer scienceBiology

Abstract

fetched live from OpenAlex

About This Issue David J. Endres In recent years, especially since the discovery of unmarked graves at Catholic-run Indian boarding schools, scholars have given increased attention to the relationship of Native Americans to the Catholic Church. This topic was further highlighted by Pope Francis's July 2022 visit to Canada, where he apologized for the Church's role in the cultural destruction and forced assimilation of Native peoples. The research presented here explores the ways that these cultural and religious systems have interacted—though not always antagonistically. They offer diverse perspectives on how Native identities have intersected with Catholicism. We are grateful to our contributors. Emma Anderson is a professor of religious studies at the University of Ottawa. Michael F. Steltenkamp, S.J., is emeritus professor of anthropology and religious studies at Wheeling University (formerly Wheeling Jesuit University) in Wheeling, West Virginia. Bryan C. Rindfleisch is an associate professor of history at Marquette University in Milwaukee, Wisconsin. Martha G. Beliveau is a graduate student in the University of Oklahoma's department of history. Paul G. Monson is vice president for intellectual formation and academic dean at Sacred Heart Seminary and School of Theology, Hales Corners, Wisconsin. Dana Lloyd is assistant professor of global interdisciplinary studies at Villanova University in Villanova, Pennsylvania. [End Page i] Copyright © 2023 The Catholic University of America Press

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)0.010
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: Editorial · Consensus signal: none
Teacher disagreement score0.602
Threshold uncertainty score0.568

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0080.005
Open science0.0020.002
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.6020.467

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 head0.017
GPT teacher head0.308
Teacher spread0.291 · 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
GenreEditorial

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
Published2023
Admission routes1
Has abstractyes

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