MétaCan
Menu
Back to cohort
Record W3130348772

So Far and Yet so Close: Frontier Cattle Ranching in Prairie Western Canada and the Northern Territory of Australia

2015· book· en· W3130348772 on OpenAlexaboutno aff
Warren M. Elofson

Bibliographic record

VenueDirectory of Open access Books (OAPEN Foundation) · 2015
Typebook
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsFrontierGeographyAgroforestryArchaeologyEnvironmental science
DOInot available

Abstract

fetched live from OpenAlex

So Far and Yet So Close provides a comparative study of frontier cattle ranching in two societies on opposite ends of the globe. It is also an environmental history that at the same time centres on both the natural and frontier environments. There are many points at which the western Canadian and northern Australian cattle frontiers evoke comparisons. Most obviously they came to life at about the same time: late 1870s-early 1880s. In both cases corporations were heavy investors and utilized an open range system in which tens of thousands of cattle roamed over thousands of square acres. Ranchers shared similar problems such as predators, disease, and weather, as well as markets. Ultimately, a nearly indistinguishable "country" culture developed in these geographically disparate and distant lands, which is still apparent today. Many similarities were in one way or another a reflection of frontier environmental conditions that is, conditions associated with the very "newness" of society. They included a lack of infrastructure (ie. fences), institutions (ie. police), and population (ie. consumers). However, the ranching people in these two societies had their differences too. In the end, the natural environment pushed agricultural development in these two regions along very different paths.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0070.002
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.046
GPT teacher head0.341
Teacher spread0.295 · 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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueDirectory of Open access Books (OAPEN Foundation)Same topicCanadian Identity and HistoryFrench-language works237,207