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Record W4409150084 · doi:10.1080/14775700.2025.2488103

“Seeing What Might Lie Beyond”: Hope and Indigenous Futurisms in Cherie Dimaline’s <i>The Marrow Thieves</i>

2025· article· en· W4409150084 on OpenAlexaboutno aff
Rebecca Tillett

Bibliographic record

VenueComparative American Studies An International Journal · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicUtopian, Dystopian, and Speculative Fiction
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousPsychologyPsychoanalysisSociologyCriminologyBiologyEcology

Abstract

fetched live from OpenAlex

This essay explores the role played by hope in an era of climate emergency, and how in Cherie Dimaline’s (Georgian Bay Métis) prize-winning novel The Marrow Thieves (2017) hope not only emerges from surviving brutal genocidal and ecocidal historical experiences of settler colonialism and capitalism, but also from actively imagining a future that is Indigenous. In taking Dimaline’s text as an example of how we can ‘see what might lie beyond’, this essay considers the increasing impossibility of ‘hope’ in the face of climate emergency, how hope is itself refracted through individual and communal lived experiences, and how Indigenous forms of hope are inevitably and profoundly impacted by both genocidal colonisation and ongoing state-supported corporate ecocide on North American Indigenous lands. Through Dimaline’s text, this essay explores how 21st-century Indigenous North American fiction draws on contentious settler colonial capitalist histories of genocide and ecocide and on contemporary Indigenous experiences of ongoing colonisation, to look to the future. In this context, I assess The Marrow Thieves as an example of Indigenous Futurism: as a means by which hope can exist in the imagining of radically different decolonial futures that centre traditional Indigenous cultural knowledges and practices.

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 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 score0.732
Threshold uncertainty score0.756

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 studies0.0010.001
Scholarly communication0.0010.001
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 head0.052
GPT teacher head0.336
Teacher spread0.284 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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