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Record W3006159613

Manufacturing Consent for an Extractive Regime in Rural New Brunswick, Canada

2019· article· en· W3006159613 on OpenAlexaffvenueabout
Mary Jo Aspinall, Susan O’Donnell, Tracy Glynn, Thomas M. Beckley

Bibliographic record

VenueJournal of rural and community development · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsMonopolySustainabilityNatural resourcePopulationPolitical scienceRural areaGeographyEconomic growthSociologyEconomicsLawDemography
DOInot available

Abstract

fetched live from OpenAlex

A common narrative for rural regions, maintained by corporate news media, is that extensive resource extraction from the natural environment by large corporations is an economic necessity. This corporate discourse marginalizes voices advocating for rural and community-based social and economic development. New Brunswick is one of the smallest and most rural provinces in Canada, with almost half of its residents living in rural areas. Our study explored how news editorials discussed rural issues in the province. News editorials function to maintain a dominant discourse in society. Unique in Canada, one family in the province has extensive business interests in resource extraction while owning a company, Brunswick News, that has a near-monopoly of the news media in the province. Our study conducted a content analysis of Brunswick News editorials focused on the term ‘rural’ over a recent five-year period. Our results highlight that in a vastly rural population, only one percent of editorials included this term. Of these, 87% backed claims of diminished rural communities, and 43% supported claims that corporate development of extractive industries was necessary to provide the economic boost to rural New Brunswick and ensure their sustainability. Keywords: news media, editorials, New Brunswick, resource extraction, diminished rural communities ---------------------------------------- Autorisation de fabrication pour un regime d'extraction dans les regions rurales du Nouveau-Brunswick, au Canada Resume Un recit commun pour les regions rurales, maintenu par les medias d'information des entreprises, est que l'extraction importante des ressources de l'environnement naturel par les grandes entreprises est une necessite economique. Ce discours corporatif marginalise les voix qui plaident pour le developpement social et economique base sur les communautes rurales. Le Nouveau-Brunswick est l'une des provinces les plus petites et les plus rurales du Canada, avec pres de la moitie de ses residents vivant en milieu rural. Notre etude a explore comment les editoriaux des nouvelles discutaient des enjeux ruraux dans la province. Les editoriaux des nouvelles ont pour fonction de maintenir un discours dominant dans la societe. Unique au Canada, une famille de la province a de vastes interets commerciaux dans l'extraction des ressources tout en etant proprietaire d'une entreprise, Brunswick News, qui detient un quasi-monopole des medias de la province. Notre etude a mene une analyse du contenu des editoriaux de Brunswick News axes sur le terme « rural » au cours d'une recente periode de cinq ans. Nos resultats soulignent que dans une population tres rurale, seulement 1% des editoriaux incluaient ce terme. De ce nombre, 87% appuyaient les revendications de collectivites rurales en declin et 43% soutenaient que le developpement des entreprises des industries extractives etait necessaire pour stimuler l'economie des regions rurales du Nouveau-Brunswick et assurer leur durabilite. Mots-cles: Medias d'information, editoriaux, Nouveau-Brunswick, extraction de ressources, communautes rurales diminuees

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)0.001
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 score0.555
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.026
GPT teacher head0.255
Teacher spread0.228 · 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
Published2019
Admission routes3
Has abstractyes

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