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Farmland Preservation: Innovative Approaches in Ontario

2005· article· en· W2514150410 on OpenAlexaboutno aff
Wayne Caldwell, Stewart G. Hilts

Bibliographic record

VenueJournal of Soil and Water Conservation · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsnot available
Fundersnot available
KeywordsLimitingAgricultureGovernment (linguistics)Agricultural economicsResource (disambiguation)GeographyAgroforestryNatural resource economicsBusinessEnvironmental protectionEnvironmental scienceEconomicsArchaeology

Abstract

fetched live from OpenAlex

Policy to protect farmland is based on the premise that it is in the public interest to protect land, farmers, and the farm economy. Within Ontario, high capability farmland is a finite resource. Ontario contains 52 percent of Canada's Class 1 land even though only 6.8 percent of the province's total land area is suitable for agriculture. The combination of quality soils with the excellent climate of Southern Ontario makes this the prime area for agricultural production in all of Canada. With an abundance of heat units and rainfall, Ontario is able to produce crops that are not viable elsewhere in the country. (Large acreages of farmland on the prairies have excellent soil, but a much more limiting climate.) The result is a diverse and active agricultural industry that led all Canadian provinces in 2001 in gross farm receipts. While the importance of Ontario's agricultural industry is generally recognized, the commitment of the public and different levels of government to its long-term protection has at times wavered. Recent developments, however, show a renewed interest on the part of the provincial government to aggressively address the issue of farmland loss. In addition, numerous groups—farmers …

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

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

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 head0.062
GPT teacher head0.221
Teacher spread0.158 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations24
Published2005
Admission routes1
Has abstractyes

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