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Record W2771286533 · doi:10.7939/r3x01m

Have Agri-Food Institutions Learned from the Bovine Spongiform Encephalopathy (BSE)

2012· article· en· W2771286533 on OpenAlexaboutno aff
Ge Song

Bibliographic record

VenueUniversity of Alberta Library · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPrion Diseases and Protein Misfolding
Canadian institutionsnot available
Fundersnot available
KeywordsBovine spongiform encephalopathyBusinessVirologyEnvironmental healthPrion proteinMedicineDiseasePathology

Abstract

fetched live from OpenAlex

In this study, representatives (n=18) from Alberta agri-food institutions were interviewed to understand the institutional learning practices that were employed following the outbreak of bovine spongiform encephalopathy (BSE) in May, 2003. Based on theoretical frameworks derived from reflexive modernization and transformative learning, this research reviewed the learning practices among different agri-food institutions in government and industry and concluded that one aspect of transformative learning, instrumental learning took place in most institutions. However, the other aspect of transformative learning, communicative learning did not occur in agri-food institutions. The study concluded the absence of communicative learning can be attributed to a lack of a rational discourse and inadequate institutional reflexivity. Based on these findings, several recommendations are offered to enhance aspects of communicative learning within agri-food institutions.

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)0.004
metaresearch head score (Gemma)0.011
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 score0.084
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.202
Teacher spread0.184 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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