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Human and Institutional Dimensions of Agroforestry

2009· book-chapter· en· W2483847342 on OpenAlex

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

VenueASSA, CSSA and SSSA · 2009
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Innovations and Practices
Canadian institutionsKamloops Art Gallery
Fundersnot available
KeywordsLivelihoodPortfolioBusinessContext (archaeology)Environmental planningEnvironmental resource managementNatural resource economicsAgricultureEconomicsGeographyFinance

Abstract

fetched live from OpenAlex

This chapter addresses the human and institutional dimensions of agroforestry. It focuses on the decision maker–the landowner–and provides a framework to understand what factors to consider when evaluating how agroforestry practices contribute to both livelihoods and the environment. The sustainable livelihoods framework is introduced to identify the assets and capitals that decision makers invest in to develop strategies in pursuit of their multiple goals. The chapter also presents the factors affecting decisions in diverse settings, from privatized to leased and licensed lands, and introduces the context of decision making and the social relations contained in the practice of agroforestry. Understanding whether household's differentiated livelihood strategies have an effect on the nature of the agroforestry practice of interest, and how the enabling environment shapes household decisions can lead to identifying pathways for adoption. Agroforestry practices in this context may be seen as a new economic opportunity that may reduce risk in the enterprise portfolio.

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 score0.768
Threshold uncertainty score0.410

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 head0.034
GPT teacher head0.242
Teacher spread0.208 · 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