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Diverse Ecological, Economic and Socio-Cultural Values of a Traditional Common Natural Resource Management System in the Moroccan High Atlas: The Aït Ikiss

2012· article· en· W2008841209 on OpenAlexaff
Pablo Domínguez, A. Bourbouze, SÉBastien Demay, Didier Génin, Nicolás Kosoy

Bibliographic record

VenueEnvironmental Values · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsSustainabilityNatural resourceNatural resource managementEnvironmental resource managementCohesion (chemistry)Ecosystem managementEcosystem servicesNatural (archaeology)GeographyEnvironmental ethicsBusinessEnvironmental planningEcologyEcosystemEconomicsArchaeology

Abstract

fetched live from OpenAlex

This study examines the multiple dimensions of the agdal system, a traditional Berber form of environmental management that regulates access to communal natural resources so as to allow the regeneration of natural resources. In fact, this ingenious system of agro-pastoral land rotation is ultimately beneficial for the conservation of the bio-physical environment, the performance of the present-day local economy and the maintenance of prevailing social cohesion and cultural coherence. Hence, agdals constitute a key element for the reinforcement of the sustainability of existing agro-pastoral societies and ecosystems, but need to be better understood in order to explore necessary adaptations in the changing world of today.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.209
Teacher spread0.189 · 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

Citations30
Published2012
Admission routes1
Has abstractyes

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