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Record W6921779180 · doi:10.7939/r3-t5rq-n180

Protecting Agricultural Land: How Informal Institutions and Historical Perspectives Affect Land-Use Policy

2022· dissertation· en· W6921779180 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2022
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicRural development and sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureStewardship (theology)Agricultural landGovernment (linguistics)Context (archaeology)Public policyAgricultural policyLand use

Abstract

fetched live from OpenAlex

Land-use pressures in Alberta's agricultural landscapes have intensified in recent years. With the province's broad historical agricultural base and ongoing urban expansion, there have been growing concerns about the loss of prime agricultural land. These concerns and conflicts have been reflected in recent provincial policies that attempt to balance competing land-use pressures. These policies include the 2008 Land-Use Framework (LUF) and the 2009 Alberta Land Stewardship Act (ALSA), which authorizes the creation of policies and management strategies to protect, conserve and enhance agricultural land (ALSA: Government of Alberta, 2009). However, local interpretations concerning province-wide land-use policies and perceived restrictions on private land use have hindered the desired outcomes (Lavelle, 2012). Since the creation of Alberta’s most recent land use policies, various studies have reported a persistent pattern of fragmentation and conversion of prime agricultural lands. While several research projects have measured the spatial context and implications of converting agricultural lands, few have attempted to assess the non-spatial causes of continuing conversion and fragmentation of agricultural land. Following a qualitative case study approach, this research aims to understand better how factors such as social norms and informal institutions influence land-use decisions at the municipal level, focusing on decisions affecting the fragmentation and conversion of agricultural land. This study also considers how these informal factors affect the application of Alberta's land-use policies and formal mandates.

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 score0.114
Threshold uncertainty score0.991

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 studies0.0010.000
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 head0.012
GPT teacher head0.188
Teacher spread0.176 · 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
Published2022
Admission routes1
Has abstractyes

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