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Record W4388453234 · doi:10.3138/chr-2022-0035

Newfoundland Mi’kmaw Resistance and Vibrancy in a History of Erasure

2023· article· en· W4388453234 on OpenAlexaffvenueabout
Mi’sel Joe, Sheila O’neill, Jocelyn Field Thorpe

Bibliographic record

VenueCanadian Historical Review · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsIndigenousResistance (ecology)DignityErasureHistoryWhite (mutation)SociologyGenealogyAestheticsGender studiesPolitical scienceLawArt

Abstract

fetched live from OpenAlex

This article is one result of Indigenous-led collaboration that challenges the erasure of Indigenous people in the history of Newfoundland. It argues that, during the nineteenth and early twentieth centuries, Mi’kmaw community members were historical actors living in relationship with the land and waters that sustained them. They challenged encroachments onto their territory and travellers’ ideas about the Mi’kmaq, and they lived their own lives in their own territory with dignity, knowledge, skills, and humour. It is possible to discern these characteristics of Mi’kmaw life even within the historical record, written almost exclusively by white men, that focuses mainly on non-Indigenous people’s experiences. The article examines both writing deemed literature and writing deemed non-fiction, demonstrating that both can interrupt the historical erasure of Indigenous peoples and relationships to territory. Historians can learn from, and be inspired by, writers and scholars in a number of disciplines who, like historians, grapple with how to be responsible storytellers in the present-day while offering insight into the past.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.067
Threshold uncertainty score0.391

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0090.012
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0010.002
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 head0.030
GPT teacher head0.246
Teacher spread0.216 · 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
Published2023
Admission routes3
Has abstractyes

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