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Record W1505106772 · doi:10.1080/14735903.2006.9686009

A spatial analysis of land-use change and agriculture in eastern Canada

2006· article· en· W1505106772 on OpenAlex
Delia Bucknell, Craig J. Pearson

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Agricultural Sustainability · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRural development and sustainability
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsAgricultureGeographySustainabilityLivestockAgricultural economicsLand useProductivityDemographicsRural areaBusinessEconomic growthEconomicsForestryEcology

Abstract

fetched live from OpenAlex

Publicly available statistics regarding rural demographics, rural society and land use are presented and analysed using Geographic Information System (GIS). Our aim was to provide a quantitative basis for discussion of rural policy issues such as urban encroachment. Productivity (tonnage) of crop agriculture has increased by about 230% over 40 years while that of livestock (expressed as livestock units) has remained constant. Agricultural consolidation and intensification seen in southern Ontario has not translated into economic sustainability where on-farm income declined from 1991 to 2000. However, on-farm income in southern Quebec and municipalities adjacent to Toronto increased, perhaps due to the niche markets created in these regions. The increases in agricultural activity throughout southern Ontario have occurred in regions that have been designated as sites for innovation clusters, thus providing a foundation of resources for bio-based industries to expand and innovate. Reflecting on trends of demographics and production systems we conclude that rural policy should orient its geographical delineation to regional and inter-provincial scales. Our analysis indicates that rural populations and communities are sustainable but agricultural enterprises have changed radically; they have maintained or increased productivity but lost profitability. Applying a rural landscape design to the entire region would help address the sustainability of agriculture and rural communities.

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.

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 score0.150
Threshold uncertainty score0.317

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.010
GPT teacher head0.214
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