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The New Pyrenees: Contemporary Conflicts around Patrimony, Resources and Urbanization

2008· article· en· W2071526772 on OpenAlexaff
Ismael Vaccaro, O. Beltrán

Bibliographic record

VenueJournal of the Society for the Anthropology of Europe · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsMcGill University
Fundersnot available
KeywordsTourismUrbanizationGeographyNatural resourceSettlement (finance)SpeculationEconomic impact analysisEconomyPolitical scienceEconomic growthBusinessEconomicsArchaeology

Abstract

fetched live from OpenAlex

Abstract In the last twenty years the Pyrenean social landscape has experienced a significant change associated with shifts on the uses of its natural resources. Communities previously characterized by their high rates of depopulation are now in a process of relative demographic recovery. This change is associated to a shift from primary economic activities such as ranching, timber extraction or agriculture to an economic model based on leisure and services. In other words, the current Pyrenees are not dominated by agro‐ranching practices. Nowadays the range is increasingly occupied by economic and social initiatives devoted to foster tourism and to cover the needs of visitors. In Spain this change has connected areas of the periphery of the countryside with its urban markets. It has moved the area from a set of marginal and unprofitable economic activities to a highly profitable market based on seasonal tourism and territorial speculation. The economic and symbolic reconstruction of the mountains from pastures into ski runs, for instance, has revealed all their economic potential in this globalized era of ours. This paper is focused in the Pallars Sobirà, a Western district of the Catalan Pyrenees. It explores the consequences of this reconfiguration of the natural resources of an area. Nature becomes patrimony: it is either protected through conservation policies designed by the state, or exploited by local or external corporations. In any case, these recent changes are having significant impacts on settlement patterns, community identity, and public policies.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.007
Scholarly communication0.0050.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.229
Teacher spread0.202 · 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 designObservational
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

Citations11
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Society for the Anthropology of EuropeSame topicConservation, Biodiversity, and Resource ManagementFrench-language works237,207