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Record W1601865490 · doi:10.15581/012.8.27783

La gestión del patrimonio arqueológico: un futuro abierto para Navarra

2018· article· es· W1601865490 on OpenAlexaff
Ma Ángeles Querol

Bibliographic record

VenueCuadernos de Arqueología de la Universidad de Navarra · 2018
Typearticle
Languagees
FieldSocial Sciences
TopicArchaeology and Cultural Heritage
Canadian institutionsImpact
Fundersnot available
KeywordsHumanitiesGeographyPolitical scienceCartographyArt

Abstract

fetched live from OpenAlex

En estos momentos, doce Comunidades Autónomas y el propio Estado español han aprobado Leyes sobre Patrimonio Histórico o Cultural. Navarra todavía no lo ha hecho. La experiencia de redacción, aprobación y aplicación de esos textos legales es una buena base para proponer una serie de análisis, comentarios y recomendaciones especialmente aplicables al Patrimonio Arqueológico, que puedan, en su caso, ser tenidas en cuenta a la hora de elaborar una posible Ley de Navarra. 
 Con este objetivo se analiza el tema de las denominaciones, los grados de protección, la Evaluación del Impacto Ambiental, las relaciones entre el Patrimonio Histórico/Cultural y el Planeamiento territorial, las previsiones sobre la Educación, la protección de los lugares en los que se sospecha la existencia de restos arqueológicos, las nuevas figuras arqueológicas como Zonas de Reserva o Parques Arqueológicos, un aspecto muy concreto de la normativa sobre hallazgos casuales, la respuesta de algunas Comunidades al controvertido tema de los detectores de metales y las regulaciones sobre intervenciones o actuaciones arqueológicas. 
 Se termina llamando la atención sobre el hecho de que lo verdaderamente importante no es tanto un adecuado texto legal como una verdadera y firme voluntad política de ponerlo en práctica.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.558
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0020.009
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.300
Teacher spread0.288 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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