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Record W2290811927 · doi:10.14288/1.0093191

Land use change in the orchard areas of the Okanagan Valley of British Columbia : a case study

2010· article· en· W2290811927 on OpenAlexaffabout
Kenneth Bradford Marshall

Bibliographic record

VenuecIRcle (University of British Columbia) · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgroforestry and silvopastoral systems
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOrchardGeographyLand use, land-use change and forestryForestryLand useArchaeologyAgricultureEcologyEngineeringCivil engineering

Abstract

fetched live from OpenAlex

The renewed interest in the preservation of agricultural land in British Columbia, brought about by the agricultural land freeze in December 1972 and the passage of Bill 42, the Land Commission Act in April 1973; established an interesting environment in which to analyze land use change in the Okanagan Valley. The loss of commercial orchard land in the Penticton area to residential and recreational uses had caused the Planning Director of the Okanagan-Similkameen Regional District to require that all major development must be made under a land use contract. This relatively new planning tool had been used in an orchard area near Penticton. This thesis is primarily a micro-economic analysis of the land use and changes to that use in this area. It is a case study which discusses the reasons behind the desire to change the land use, the effects of the marketing organization of the tree-fruit industry and governmental influences which affect the industry as a whole. The International problems affecting the tree-fruit industry are also analyzed as is their effect on the individual orchardist. The contention of this study is that although Bill 42 may have attempted to correct one of the symptoms of an ailing industry, more effort will have to be extended to eliminate the causes.

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 score0.068
Threshold uncertainty score0.223

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 communication0.0000.000
Open science0.0010.000
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 head0.023
GPT teacher head0.183
Teacher spread0.160 · 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

Citations0
Published2010
Admission routes2
Has abstractyes

Explore more

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