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Record W2744645957 · doi:10.15359/rh.75.1

Bosques, fincas y ciudades. Un acercamiento al proceso socio-metabólico de apropiación en la Región Norte de Costa Rica (1909-1955)

2017· article· es· W2744645957 on OpenAlexaff
Anthony Goebel Mc Dermott

Bibliographic record

VenueRevista de Historia · 2017
Typearticle
Languagees
FieldEnvironmental Science
TopicWater-Energy-Food Nexus Studies
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsHumanitiesGeographyPhilosophy

Abstract

fetched live from OpenAlex

Desde la perspectiva del metabolismo social, el proceso sociometabólico de apropiación se constituye en la forma primaria de intercambio entre la sociedad humana y la naturaleza. En este proceso, las sociedades se apropian de materiales, energías y servicios requeridos por los seres humanos y sus artefactos, desarticulando o desorganizando los ecosistemas y reorganizándolos con fines productivos. A partir de estas premisas, el presente análisis procuró dar cuenta de las principales transformaciones socio-ecológicas que tuvieron lugar en la Región Norte de Costa Rica, caracterizada por una incorporación lenta, tardía e incompleta al proyecto económico, social y político emanado desde el Valle Central. La explotación forestal primero, y la ganadería después, ambas actividades con una clara vocación comercial, se constituyeron en las alternativas económicas predominantes en la región, aún con marcadas diferencias intrarregionales. Esta “apropiación mercantilista” de la naturaleza, que se instauró desde los propios inicios de la colonización efectiva del territorio, trajo consigo profundas consecuencias ecológicas y ambientales, como la pérdida de biodiversidad, la simplificación de los ecosistemas, el empobrecimiento de nutrientes de los suelos, la reducción de las funciones ecológicas del bosque y, en general, la degradación de los ecosistemas.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.547
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.012
GPT teacher head0.256
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 teacher head, not a consensus.

Study designNot applicable
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

Citations1
Published2017
Admission routes1
Has abstractyes

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