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Record W2896425056

“Like oil and water”: extractive industry, water rights, and aesthetic activism in native american interactive digital narrative

2018· article· en· W2896425056 on OpenAlexaboutno aff
Deborah L. Madsen

Bibliographic record

VenueArchive ouverte UNIGE (University of Geneva) · 2018
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsOpposition (politics)IndigenousPoliticsEnvironmentalismPolitical scienceLawEconomyPolitical economySociologyEconomics
DOInot available

Abstract

fetched live from OpenAlex

Idiomatic English expressions such as “oil and water don't mix” or “like oil and water” – to describe a profound incompatibility – take on a specific political meaning in the context of water rights and Indigenous opposition to the extractive oil industry. Most recently, opposition to the Dakota Access Pipeline (the #NoDAPL movement, which started in 2016) highlights the threat to clean water supplies to the Standing Rock Sioux Indian Reservation. Originally planned to run further north, near the city of Bismarck, North Dakota and thus avoiding the reservation, the pipeline route was changed because of the risk of toxic crude-oil leakage into the city's water supply. This redirection – and the transfer of risk from US to Sioux communities – has been termed “environmental racism” and an expression of “environmental colonialism” by activists, to which is added the charge of cultural genocide because construction of the pipeline desecrates tribal burial grounds and has destroyed other sites of sacred and archeological value. NoDAPL protesters emphasize that while the environmental threat posed by the pipeline impacts the Sioux Nation most immediately, it is not restricted to the Standing Rock Reservation but affects the quality of water supplies to all communities downstream of the point where the pipeline crosses the Missouri River. The powerful public response to the NoDAPL movement – by Indigenous activists and non-Indigenous allies – was provoked in important ways by the mobilization of social media specifically and digital media more generally. Evoking the title of the United Nations International Decade for Action (2005-2015) – “Water for Life” – activists gathered, physically at Standing Rock and virtually through online platforms, under the slogan "Mni Wichoni" – “Water is Life” – to protest environmental destruction, the erasure of Sioux tribal sovereignty (Sioux jurisdiction over the Missouri River and its shorelines as defined by the 1851 Treaty of Fort Laramie, affirmed by the US Supreme Court in 1904) by the US Army Corps of Engineers, and also the global threat to water posed by extractive industries. A significant recent deployment of digital media to raise public consciousness of such urgent environmental issues is Anishinaabe/Métis artist Elizabeth LaPensée's Open Access video-game Thunderbird Strike (2017), which has been condemned by Republican Minnesota State Senator David Osmek as “an eco-terrorist version of Angry Birds.” The game uses interactive digital narrative to perform Indigenous concepts of environmental care-taking and social justice, concepts that motivate ethical action – if only within the virtual diegetic environment of the game-world. This presentation engages the notion of “aesthetic activism,” in the context of “social impact” video-games, by exposing the primary narrative strategies by which the player is positioned in the virtual role of “eco-terrorist” or Water Protector. By rehearsing a restorative Indigenous relation to the environment and other-than-human nature, based on the values of respect, reciprocity, and preservation, Thunderbird Strike proposes an alternative to exploitative, colonialist, and literally toxic valuations of environment.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.999

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 studies0.0020.002
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.013
GPT teacher head0.274
Teacher spread0.260 · 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 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
Published2018
Admission routes1
Has abstractyes

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