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Between Forestry and Farming: Policy and Environmental Implications of the Barriers to Agroforestry Adoption

2012· article· en· W2165721685 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomie · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsnot available
FundersAgricultural Research ServiceU.S. Department of AgricultureU.S. Environmental Protection Agency
KeywordsAgricultureAgroforestryBusinessForestryAgricultural economicsGeographyEnvironmental scienceEconomics

Abstract

fetched live from OpenAlex

Farming and forestry are practices with clearly defined institutions, markets, and policies. These are not as clearly defined for agroforestry, a practice experiencing increased interest in the USA. This study examined the barriers preventing the adoption of agroforestry within a household level theoretical framework informed by transaction costs and multifunctionality, using survey data from 353 Missouri (USA) landowners. Costs of establishing or managing trees, the time required to manage, and the lack of tree management experience are perceived as the most influential barriers limiting implementation of agroforestry on the farm. A principal component factor analysis of the perceived barriers identified two factors: the first, labeled Transaction Costs, related to information access and perceived establishment costs; the second factor, labeled Profitability Concerns, was associated with perceptions of the effects of agroforestry on farm profitability and agricultural production. Overall, Transaction Costs appears to be a greater barrier to implementation of agroforestry. Cluster analysis yielded three types of landowners: environmentalists, agriculturalists, and disengaged, who differ in their perceptions of these barriers. Statistical tests revealed differences among clusters on their farmland attributes, multifunctionality indicators, and their resources for adopting agroforestry. Environmentalists appear as more likely to adopt agroforestry, followed by the agriculturalists. Policy implications are also discussed. Les secteurs de l’agriculture et de la foresterie possèdent des institutions, des marchés et des politiques clairement définis. Ces éléments ne sont pas aussi clairement définis dans le cas du secteur de l’agroforesterie, qui recueille un intérêt croissant aux États‐Unis. Dans la présente étude, nous avons examiné les obstacles à l’adoption de l’agroforesterie à l’aide d’un cadre théorique au niveau des ménages comprenant des données sur les coûts de transaction et la multifonctionnalité issues d’un sondage réalisé auprès de 353 propriétaires fonciers dans l’État du Missouri, aux États‐Unis. Les coûts de plantation, le temps nécessaire à la gestion et le manque d’expérience en gestion arboricole sont perçus comme étant les principaux obstacles à l’implantation de l’agroforesterie sur la ferme. Une analyse en composantes principales a permis de déterminer deux facteurs : le premier, appelé Coûts de transaction (Transaction Costs), était liéà l’accès à l’information et aux coûts de plantation perçus; le deuxième, appelé Inquiétudes sur la rentabilité (Profitability Concerns), était liéà la perception des conséquences de l’agroforesterie sur la rentabilité et la production de la ferme. De manière générale, les Coûts de transaction semblent constituer le plus important obstacle à l’implantation de l’agroforesterie. Une analyse de grappes a fait ressortir trois types de propriétaires fonciers : les environnementalistes, les agriculturalistes et les désengagés, qui ont une perception bien différente de ces obstacles. Des tests statistiques ont révélé des différences parmi les grappes quant aux attributs de leurs terres agricoles, aux indicateurs de multifonctionnalité et à leurs ressources pour adopter l’agroforesterie. Les Environnementalistes semblent plus enclins à adopter l’agroforesterie, suivis des Agriculturalistes. Nous avons aussi abordé l’incidence sur les politiques.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score0.982

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 head0.013
GPT teacher head0.173
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