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The social representation and reality of BSE's impact in North Central Alberta

2008· article· en· W2021138003 on OpenAlexvenueaboutno aff
Michael J. Broadway

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2008
Typearticle
Languageen
FieldPsychology
TopicSocial Representations and Identity
Canadian institutionsnot available
Fundersnot available
KeywordsBovine spongiform encephalopathyOutbreakRepresentation (politics)Government (linguistics)GeographyCommoditySocioeconomicsDiseaseEconomyBusinessPolitical scienceEconomicsMedicineLaw

Abstract

fetched live from OpenAlex

Bovine Spongiform Encephalopathy (BSE), popularly known as ‘Mad Cow’ disease, was discovered in the late 1980s in Britain; in 1996, scientists announced a ‘probable’ link between eating BSE‐contaminated meat and a new form of Creutzfeldt‐Jakob disease, a fatal human brain disease. Britain's beef industry was devastated, beef consumption dropped, export markets closed and a mass cull of older cattle was implemented. This article uses social representation theory to analyze how Canada's 2003 BSE outbreak was portrayed to Canadians in major newspapers and compares this representation with BSE's impact in two rural Alberta counties. The day Canada's BSE case was reported, the United States closed its border to Canadian cattle and beef. The event was represented as ‘devastating’ to Canada's cattle and beef industries and rural areas in general, a view that went largely unchallenged and was critical to gaining government support for the affected industries. Little evidence of economic devastation was found in the heart of Alberta's cow‐calf producing area; producers adapted to their changing economic circumstances and acquired other sources of income. But there is little doubt that the financial uncertainty associated with BSE added to stress levels among farm families .

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.896

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0010.002
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 head0.021
GPT teacher head0.291
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2008
Admission routes2
Has abstractyes

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