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Record W4389640314 · doi:10.3138/cjc-2022-0004

“Invading Indigenous Territory is Not Reconciliation”: Problematizing War Frames in News Coverage of Wet’suwet’en Solidarity Actions

2023· article· en· W4389640314 on OpenAlexaffvenueabout
Rebecca Hume, Kevin Walby

Bibliographic record

VenueCanadian Journal of Communication · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsSolidarityFraming (construction)IndigenousMainstreamPolitical scienceColonialismSociologyMedia studiesSovereigntyOperationalizationGender studiesLawGeographyPoliticsEpistemology

Abstract

fetched live from OpenAlex

Context: Leading up to the March 2020 global COVID-19 lockdown, an important movement was building power across so-called Canada. What began as a continuation of the decades-long, localized struggle for self-determination in Wet’suwet’en territory quickly became a focal point for nationwide Indigenous resistance, refusal, and solidarity. Analysis: Drawing from literature on media framing, this article examines the use of war frames in early 2020 news depictions of mobilizations in solidarity with Wet’suwet’en. The analysis suggests that war frames are operationalized to simultaneously naturalize police violence while also validating the sovereignty of Indigenous nations. Conclusion and implications: This work contributes not only to the literature on the framing of protests by the mainstream media but also to the ongoing project of unsettling conditions of settler colonial power in Canadian society.

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)0.005
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.597
Threshold uncertainty score0.801

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0130.016
Scholarly communication0.0120.005
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.047
GPT teacher head0.322
Teacher spread0.276 · 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 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
Published2023
Admission routes3
Has abstractyes

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