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Record W4309865355 · doi:10.18778/2083-2931.12.13

Apocalypse When? Storytelling and Spiralic Time in Cherie Dimaline’s The Marrow Thieves and Louise Erdrich’s Future Home of the Living God

2022· article· en· W4309865355 on OpenAlexaboutno aff
Emily Childers, Hannah Menendez

Bibliographic record

VenueText Matters · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGothic Literature and Media Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsTemporalitiesStorytellingAnthropoceneIndigenousNarrativeColonialismHistoryEnvironmental ethicsAestheticsSociologyPolitical scienceArtLiteratureLawArchaeologyEcologyPhilosophy

Abstract

fetched live from OpenAlex

Contemporary climate fiction (cli-fi) frequently invokes the concept of apocalypse to explore the experience of living through the era of unprecedented climate change and environmental disaster that has been named the Anthropocene. Yet, as often as apocalyptic narratives are deployed to express those anxieties and experiences, they so often ignore the histories and presents of peoples who have already lived through multiple apocalypses—in particular, the ongoing violence of settler colonial exploitation of the land now called North America. Considering the role that settler colonialism has played in the development of the current crisis, we turn to two recent works by the Métis writer Cherie Dimaline and Ojibwe author Louise Erdrich to consider how the act of cultural storytelling challenges Western notions of linear temporalities. Our analysis of Dimaline’s The Marrow Thieves will explore how the settler-colonial narratives of scientific progress is challenged through Indigenous storytelling and collective memory, and our analysis of Erdrich’s Future Home of the Living God will examine how Indigenous modes of understanding operate through a cyclical timescape that allows for alternative methods of existing with and within the larger world.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.624
Threshold uncertainty score0.468

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.006
GPT teacher head0.215
Teacher spread0.209 · 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.

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

Citations1
Published2022
Admission routes1
Has abstractyes

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