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Record W4388769044 · doi:10.1515/9781552384329

The Prairie West as Promised Land

2007· book· en· W4388769044 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Calgary Press eBooks · 2007
Typebook
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceGeographyArchaeologyForestry

Abstract

fetched live from OpenAlex

So the emblem of the West Our bright Maple Leaf is bless'd To its children of the goodly open hand; All the nations of the earth Are now learning of its worth And are flocking to this wealthy, promised land. - The Sugar Maple Tree Song, 1906 In 1906, the Sugar Maple Tree Song was just one example of the rhapsodic pieces that touted the Prairie West as the "promised land." In the formative years of agricultural settlement from the late nineteenth century to the First World War, the Canadian government, along with the railways and other Prairie boosters, further developed and propagated this image within the widely distributed promotional literature that was used to attract millions of immigrants to the Canadian West from all corners of the world. Some saw the Prairies as an ideal place to create a Utopian society; others seized the chance to take control of their own destinies in a new and exciting place. The image of the West as a place of unbridled prosperity and opportunity became the dominant perception of the region at that time. During the interwar and post-World War II eras, this image was questioned and challenged, although not entirely replaced, thus showing its pervasive influence.The Prairie West as Promised Land is group of essays, which includes contributions from some of the best-known Prairie historians as well as some of the most promising new scholars in the field, explores this persistent theme in Prairie history and makes an important contribution to the historiography of the Canadian West. With Contributions By: Sarah Carter Catherine A. Cavanaugh Brett Fairbairn Michael Fedyk R. Douglas Francis David Hall SteveHewitt Laurence Kitzan Chris Kitzan George Melnyk Doug Owram Anthony W. Rasporich Bradford J. Rennie Bill Waiser Matthew Wangler Randi Warne

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)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.904
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.012
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.009
GPT teacher head0.171
Teacher spread0.162 · 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".

Quick stats

Citations2
Published2007
Admission routes1
Has abstractyes

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