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Oka-Nada

2025· book-chapter· en· W7084115020 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Press of Mississippi eBooks · 2025
Typebook-chapter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsZombieIndigenousNarrativeVariety (cybernetics)State (computer science)Jungle

Abstract

fetched live from OpenAlex

There has been a recent proliferation of Indigenous-made zombie narratives that blend traditional Indigenous knowledge with contemporary monsters using a technique that Teresa A. Goddu calls “haunting back.” “Haunting Back” allows these narratives to interrupt Canadianism and its role in ongoing colonization, thus disrupting historical contagion and providing Indigenous storytellers with the opportunity to reclaim bits of the history that has silenced, misrepresented, and caused violence to them. For example, in the 2019 Mi’kmaq film, <italic>Blood Quantum, </italic>Indigenous peoples are immune to the zombie pathogen. Immunity opens up space for the film to haunt back against a variety of historical conflicts that Canada has used to define itself, such as the Cabot foundation myth, the 1981 raids at Restigouche, and the 1990 Oka crisis. Ultimately, films like <italic>Blood Quantum</italic> unveil how the history of Turtle Island (North America) is predicated on the silencing of Indigenous peoples, and they are finally writing (haunting) back.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.716
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.184
Teacher spread0.174 · 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 teacher head, not a consensus.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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