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Learning from Food Laws in Nova Scotia

2019· book-chapter· en· W4244458481 on OpenAlexaboutno aff
Rachel B. Herrmann

Bibliographic record

VenueCornell University Press eBooks · 2019
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsNova scotiaFamineWhite (mutation)MainlandGeographyFood securityPolitical scienceLawAgricultureArchaeologyBiology

Abstract

fetched live from OpenAlex

This chapter addresses black hunger in Nova Scotia. When white Loyalists fled the mainland American colonies, they transported ideas about hunger prevention with them. As refugee colonists, they advocated for food aid based on their knowledge of previous colonization efforts. In Nova Scotia, they blocked black colonists' access to land while taking more of it for themselves, and they enacted food laws to avoid famine. Their actions became a way to fight white hunger while ignoring—and sometimes creating—black hunger. Because white Loyalists interfered with black people's food choices while keeping them from obtaining land, their actions in Nova Scotia can be characterized as victual imperialism. These food laws were so consequential because they stopped black colonists from producing and obtaining edible commodities using the methods that had previously worked in land-scarce environments. Ultimately, black hunger was a product of several factors: inadequate planning prior to migrants' arrival in the province, land dearth, distance from food-aid distribution centers, unfavorable weather, and, finally, the introduction of laws controlling bread production, fish harvesting, and marketing practices.

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)0.000
metaresearch head score (Gemma)0.000
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.193
Threshold uncertainty score0.389

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.044
GPT teacher head0.185
Teacher spread0.141 · 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
GenreOther

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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Same venueCornell University Press eBooksSame topicCanadian Identity and HistoryFrench-language works237,207