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Record W2994881570 · doi:10.7202/1065595ar

“Milking” the Consumer?

2019· article· en· W2994881570 on OpenAlexvenueaboutno aff
Andrew Ebejer

Bibliographic record

VenueOntario History · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsProduct (mathematics)Profit (economics)Government (linguistics)BusinessEconomicsPer capitaMilkingMarketingMarket economyCommerceAgricultural economics

Abstract

fetched live from OpenAlex

In the early 1930s, Ontario’s milk industry was crippled by a series of “price wars” that undermined the profit-making ability of both milk producers and distributors. The province responded to this untenable situation by creating the Ontario Milk Control Board (MCB), which eventually stabilized the industry through licensing, bonding, and fixed price agreements. Congruent to this stabilization was the gradual inflation of consumer milk prices—much to the angst of a consuming public that found it difficult to subsist. Communists and housewives alike protested in Ontario cities. Alternative, sometimes radical, solutions were proposed. Consumer advocates additionally sought a pure and nutritious product for their undernourished children. Debates over pasteurization, in particular, raged alongside boycotts over cost. Yet, this emerging consumer movement attracted little government support and enjoyed only marginal success. Producers and dairies successfully mobilized the MCB on their behalf, whereas consumers failed to achieve price concessions and were often constrained by the state.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.067
Threshold uncertainty score0.486

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0210.020
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0120.002

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 head0.013
GPT teacher head0.191
Teacher spread0.177 · 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 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

Citations2
Published2019
Admission routes2
Has abstractyes

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