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Record W4313641858 · doi:10.22136/est20231961

Limitaciones y oportunidades para el escalamiento de cuatro empresas forestales comunitarias del centro de México

2022· article· es· W4313641858 on OpenAlexaff
Leopoldo Galicia, Vidal Guerra de la Cruz, Gabriela De la Mora-De la Mora, Leslie Elizabeth Solís Mendoza, Laura Oliva Sánchez-Nupan, Ricardo Balam Castro Torres, Robert Kozak, Guillaume Peterson St‐Laurent

Bibliographic record

VenueEconomía Sociedad y Territorio · 2022
Typearticle
Languagees
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPolitical scienceHumanitiesGeographyArt

Abstract

fetched live from OpenAlex

Las empresas forestales comunitarias (EFC) requieren habilidades de planificación comercial regional para establecer y mantener asociaciones comerciales a mayor escala. El objetivo de este estudio es identificar la percepción de cuatro EFC contrastantes sobre las limitaciones y oportunidades de escalamiento en el centrode México, con base en el nivel de desarrollo de aprovechamiento silvícola y organización social, aplicando entrevistas a diferentes actores. El análisis cualitativo de obstáculos y oportunidades sugiere que las estrategias de escalamiento deben fomentar capacitación técnica y administrativa, desarrollar infraestructura y gobernanza interna sólida, que favorezca la diversificación económica, y mayores ingresos derivados del manejo forestal.

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)0.002
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.028
GPT teacher head0.272
Teacher spread0.244 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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