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Record W2563945665 · doi:10.1108/ohi-02-2009-b0002

Tenure and Land Markets for Urban Agriculture

2009· article· en· W2563945665 on OpenAlex
Mark Redwood

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.

Bibliographic record

VenueOpen House International · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsInternational Development Research Centre
Fundersnot available
KeywordsLivelihoodBusinessLand titlingLand tenureSecurity of tenureOrder (exchange)AgricultureKinshipFood securityValue (mathematics)Natural resource economicsEconomic growthEnvironmental planningGeographyEconomicsFinancePolitical science

Abstract

fetched live from OpenAlex

Cities are shaped by many elements, but undoubtedly one of the most significant factors is the urban land market. Urban farmers, often producing food on land with limited or no security of tenure, are exposed to the risk of being evicted in order for land to be used for more profitable uses such as housing development. In the absence of a system of land titling, advocacy groups, or secure tenure, urban farmers are pushed to the margins. It then becomes difficult to support, manage and/or regulate the sector. More importantly, without legal status, most forms of credit are inaccessible to farmers and they must rely on kinship and illicit sources for credit. The influence of land tenure on the security of urban farmers to practice their livelihood is significant. Recent IDRC supported projects suggest that banking systems and economists need to develop a methodology to value lands that are informally controlled by farmers or where there are customary legal systems in place. Moreover, evidence suggests that advocacy groups have manage to increase security and access to land for urban 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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.399
Threshold uncertainty score0.267

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 science0.0000.000
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 head0.234
Teacher spread0.222 · 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