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Record W1534173387

Weaving chains of grain: exploring the stories, links and boundaries of small scale grain initiatives in Southwestern British Columbia

2009· dissertation· en· W1534173387 on OpenAlexfundaboutno aff
Chris Hergesheimer

Bibliographic record

VenueSummit (Simon Fraser University) · 2009
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsnot available
FundersSimon Fraser University
KeywordsSocial capitalReciprocity (cultural anthropology)WeavingEconomic geographyScale (ratio)Subsistence agricultureGeographyProcess (computing)MarketingBusinessPolitical scienceEngineeringSociologyArchaeologySocial scienceComputer scienceCartographyAgricultureMechanical engineering
DOInot available

Abstract

fetched live from OpenAlex

Grain related activities have recently appeared in southwestern British Columbia, exhibiting dynamic social histories as a result of links between landscapes, farmers, processors and consumers. Traceable social networks that assist grain’s journey from field to plate characterize these social histories, which are contingent upon information about the chain process being shared with consumers. The depth of a given social history hinges upon the “social length”, or the number of geographically proximate links that contribute to the process. Grain chains with deep social histories help strengthen existing network connections as well as assist in developing new ones. Long social networks contribute to the production of trust and reciprocity, commonly understood as social capital. Challenges facing grain chains in SW BC, including production methods, access to seeds and machinery, marketing strategies and power dynamics have engendered unique models of community-supported grain production.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0180.006
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.016
GPT teacher head0.184
Teacher spread0.168 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2009
Admission routes2
Has abstractyes

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