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Record W3159987482

Decolonization on the Salish Sea: A Tribal Journey back to Mormon Studies

2018· article· en· W3159987482 on OpenAlexaboutno aff
Thomas Murphy

Bibliographic record

VenueSSRN Electronic Journal · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicMormonism, Religion, and History
Canadian institutionsnot available
Fundersnot available
KeywordsDecolonizationIndigenousColonialismUndoingBELLAEthnographyNarrativeIdentity (music)Gender studiesHistoryEthnologyAnthropologySociologyPolitical scienceAestheticsArtLawLiteratureArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Decolonization is vital to undoing the legacy of racism and colonialism in today’s world but is also challenging work that is tasking for the researcher and those with whom we work. This auto-ethnographic narrative offers important lessons for the decolonization of Mormonism. It highlights the experiences of Thomas Murphy as he has navigated the terrain of Mormon Studies early in his career, shifted focus to decolonization projects on the Salish Sea, and returns again to look at Mormonism anew. Murphy reflexively examines his own identity as a light-skinned Mormon raised with stories of Indigenous ancestry and the inspiration these gave for ethnographic fieldwork among Mayan, Ladino, Nahua, Zapotec and Coast Salish communities. He draws from his experiences on the Tribal Canoe Journey’s 2014 Paddle to Bella Bella, British Columbia in Canada to offer a vision for a decolonized Mormonism, one in which Indigenous sovereignty is respected and artifacts associated with the production of Mormon scripture are repatriated. In the process of decolonizing ourselves, he argues, we need to deconstruct Lamanite identity, reconsider our truth claims, and move Indigenous voices to the center of our analysis.

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)0.002
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.315

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0330.019
Scholarly communication0.0050.003
Open science0.0010.009
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.040
GPT teacher head0.264
Teacher spread0.224 · 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
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

Citations3
Published2018
Admission routes1
Has abstractyes

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Same venueSSRN Electronic JournalSame topicMormonism, Religion, and HistoryFrench-language works237,207