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Record W4391000113 · doi:10.1515/9781571138774

The Farm Novel in North America

2013· book· en· W4391000113 on OpenAlexaboutno aff
Florian Freitag

Bibliographic record

VenueBoydell and Brewer eBooks · 2013
Typebook
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsnot available
Fundersnot available
KeywordsGeography

Abstract

fetched live from OpenAlex

Provides the first history of the North American farm novel, a genre which includes John Steinbeck's The Grapes of Wrath , Sheila Watson's The Double Hook , and Louis Hémon's Maria Chapdelaine . From John Steinbeck's The Grapes of Wrath and Martha Ostenso's Wild Geese to Louis Hémon's Maria Chapdelaine , some of the most famous works of American, English Canadian, and French Canadian literature belongto the genre of the farm novel. In this volume, Florian Freitag provides the first history of the genre in North America from its beginnings in the middle of the nineteenth century to its apogee in French Canada around the middleof the twentieth. Through surveys and selected detailed analyses of a large number of farm novels written in French and English, Freitag examines how North American farm novels draw on the history of farming in nineteenth-centuryNorth America as well as on the national self-conceptions of the United States, English Canada, and French Canada, portraying farmers as national icons and the farm as a symbolic space of the American, English Canadian, and FrenchCanadian nations. Turning away from traditional readings of farm novels within the frameworks of regionalism and pastoralism, Freitag takes a comparative look at a genre that helped to spatialize North American national dreams. Florian Freitag is Assistant Professor of American Studies at the University of Mainz, Germany.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.069
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.003
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.007
GPT teacher head0.164
Teacher spread0.157 · 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 designTheoretical or conceptual
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".

Quick stats

Citations4
Published2013
Admission routes1
Has abstractyes

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Same venueBoydell and Brewer eBooksSame topicAmerican Environmental and Regional HistoryFrench-language works237,207