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Record W2807026069 · doi:10.1177/2514848618777621

Indigenous science (fiction) for the Anthropocene: Ancestral dystopias and fantasies of climate change crises

2018· article· en· W2807026069 on OpenAlexaboutno aff
Kyle Powys Whyte

Bibliographic record

VenueEnvironment and Planning E Nature and Space · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicEcocriticism and Environmental Literature
Canadian institutionsnot available
Fundersnot available
KeywordsDystopiaAnthropoceneIndigenousNarrativeClimate changeEnvironmental ethicsColonialismHistorySociologyPolitical scienceLawEcologyLiteratureArchaeologyArtPhilosophy

Abstract

fetched live from OpenAlex

Portrayals of the Anthropocene period are often dystopian or post-apocalyptic narratives of climate crises that will leave humans in horrific science-fiction scenarios. Such narratives can erase certain populations, such as Indigenous peoples, who approach climate change having already been through transformations of their societies induced by colonial violence. This essay discusses how some Indigenous perspectives on climate change can situate the present time as already dystopian. Instead of dread of an impending crisis, Indigenous approaches to climate change are motivated through dialogic narratives with descendants and ancestors. In some cases, these narratives are like science fiction in which Indigenous peoples work to empower their own protagonists to address contemporary challenges. Yet within literature on climate change and the Anthropocene, Indigenous peoples often get placed in historical categories designed by nonIndigenous persons, such as the Holocene. In some cases, these categories serve as the backdrop for allies' narratives that privilege themselves as the protagonists who will save Indigenous peoples from colonial violence and the climate crisis. I speculate that this tendency among allies could possibly be related to their sometimes denying that they are living in times their ancestors would have likely fantasized about. I will show how this denial threatens allies' capacities to build coalitions with Indigenous peoples. Inuit culture is based on the ice, the snow and the cold…. It is the speed and intensity in which change has occurred and continues to occur that is a big factor why we are having trouble with adapting to certain situations. Climate change is yet another rapid assault on our way of life. It cannot be separated from the first waves of changes and assaults at the very core of the human spirit that have come our way. Just as we are recognizing and understanding the first waves of change … our environment and climate now gets threatened. Sheila Watt-Cloutier, interviewed by the Ottawa Citizen. (Robb, 2015) In North America many Indigenous traditions tell us that reality is more than just facts and figures collected so that humankind might widely use resources. Rather, to know “it”—reality—requires respect for the relationships and relatives that constitute the complex web of life. I call this Indigenous realism, and it entails that we, members of humankind, accept our inalienable responsibilities as members of the planet's complex life system, as well as our inalienable rights. ( Wildcat, 2009 , xi) Within Māori ontological and cosmological paradigms it is impossible to conceive of the present and the future as separate and distinct from the past, for the past is constitutive of the present and, as such, is inherently reconstituted within the future. (Stewart-Harawira, 2005, 42) In fact, incorporating time travel, alternate realities, parallel universes and multiverses, and alternative histories is a hallmark of Native storytelling tradition, while viewing time as pasts, presents, and futures that flow together like currents in a navigable stream is central to Native epistemologies. ( Dillon, 2016a , 345)

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0210.034
Scholarly communication0.0070.007
Open science0.0010.005
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.025
GPT teacher head0.260
Teacher spread0.234 · 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 designTheoretical or conceptual
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

Citations737
Published2018
Admission routes1
Has abstractyes

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