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Record W4417270764 · doi:10.1353/bh.2025.a976870

Farm to Table Reading: Industrial Agriculture and Media Materiality in the Twentieth Century

2025· article· en· W4417270764 on OpenAlexaboutno aff
Michael Stamm

Bibliographic record

VenueBook history · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsNewspaperJeffersonian democracyEconomic nationalismCommodityCommissionRevenueTourismAgricultureCommodification

Abstract

fetched live from OpenAlex

Abstract: Following a period of profligate pulpwood logging that threatened domestic forest resources, a 1911 change in North American tariff policy made Canadian newsprint a duty-free import to the United States. While this gave newspaper publishers subsidized access to plentiful paper supplies, it also generated fears that the functioning of the American press was now dependent on a commodity produced in a foreign country. As part of a nationalist mood in the US in the 1920s, some sought to find new sources of domestic raw materials from which to manufacture paper, and Midwestern cornstalks were among the most promising options. By the late 1920s, the United States Department of Agriculture and private firms had proven the concept that corn paper was a practically viable alternative to imported Canadian wood paper, and a series of Midwestern newspapers did demonstration printings of editions meant to model what they believed to be both the future of newspaper publishing and the future of farming. The successful demonstrations were meant to show resource sovereignty over the material basis of public life and to assert that US newspapers could thrive using domestic resources. It was possible, many believed, to have farm to table reading in the heartland.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.083
Threshold uncertainty score0.573

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0210.025
Scholarly communication0.0130.003
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0210.001

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 head0.020
GPT teacher head0.223
Teacher spread0.203 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueBook historySame topicCanadian Identity and HistoryFrench-language works237,207