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Record W2343347744 · doi:10.1080/00076791.2016.1173031

The problem of milk in the nineteenth-century Ontario cheese industry: an envirotechnical approach to business history

2016· article· en· W2343347744 on OpenAlex
Hayley Goodchild

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBusiness History · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsMcMaster University
Fundersnot available
KeywordsScale (ratio)Dairy industryProduction (economics)Relevance (law)BusinessFood spoilageEconomyMarketingEconomicsPolitical scienceGeographyFood scienceLawBiology

Abstract

fetched live from OpenAlex

This article analyses Ontario’s export-oriented cheese industry and its challenges in the second half of the nineteenth century using an ‘envirotechnical’ approach. The reorganisation of cheese production from farms to rural factories in the 1860s increased opportunities for spoilage and adulteration of milk at the same time that it made detecting and managing the same more difficult, which compelled the provincial dairymen’s associations to develop quasi-managerial roles to contend with these unanticipated challenges. The ‘problem of milk’ highlights the extent to which the rural cheese industry was an ecological and envirotechnical process rather than an entity separate from the non-human world. Ultimately this case study offers one model for combining environmental and business histories at a scale beyond the individual firm while also highlighting the relevance of the local in the development of the global food system in the late-nineteenth century.

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.

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 score0.442
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.028
GPT teacher head0.179
Teacher spread0.151 · 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