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Record W2567330055 · doi:10.15353/cfs-rcea.v3i2.149

Heroes for the helpless: A critical discourse analysis of Canadian national print media’s coverage of the food insecurity crisis in Nunavut

2016· article· en· W2567330055 on OpenAlexafffundvenueabout
Bradley Hiebert, Elaine Power

Bibliographic record

VenueCanadian Food Studies / La Revue canadienne des études sur l alimentation · 2016
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsWestern University
FundersArcticNetMcGill University
KeywordsGlobeNewspaperPovertyCritical discourse analysisFood insecurityPolitical sciencePrint mediaPosition (finance)Development economicsEconomic growthMedia studiesGeographySociologyFood securityPsychologyPoliticsBusinessLawEconomicsIdeology

Abstract

fetched live from OpenAlex

In northern Canada, the Inuit’s transition from a culturally traditional to a Western diet has been accompanied by chronic poverty and provoked high levels of food insecurity, resulting in numerous negative health outcomes. This study examines national coverage of Nunavut food insecurity as presented in two of Canada’s most widely read newspapers: The Globe and Mail and National Post. A critical discourse analysis (CDA) was employed to analyze 24 articles, 19 from The Globe and Mail and 5 from National Post. Analysis suggests national print media propagates the Inuit’s position as The Other by selectively reporting on social issues such as hunger, poverty and income. Terms such as “Northerners” and “Southerners” are frequently used to categorically separate Nunavut from the rest of Canada and Inuit-driven efforts to resolve their own issues are widely ignored. This effectively portrays the Inuit as helpless and the territory as a failure, and allows Canadians to maintain colonialist views of Inuit inferiority and erroneously assume Federal initiatives effectively address Northern food insecurity.

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)0.011
metaresearch head score (Gemma)0.020
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 score0.108
Threshold uncertainty score0.780

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0070.007
Science and technology studies0.0450.032
Scholarly communication0.0150.005
Open science0.0030.006
Research integrity0.0030.005
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 head0.091
GPT teacher head0.361
Teacher spread0.270 · 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

Citations4
Published2016
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Food Studies / La Revue canadienne des études sur l alimentationSame topicIndigenous Studies and EcologyFrench-language works237,207