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Record W7081544471

Aspectos religiosos de las exhumaciones / Religious Aspects of Mass grave Exhumations. Panel 4 del congreso "Cuerpos incómodos: Violencia masiva, fosas comunes y necropolítica"

2018· article· es· W7081544471 on OpenAlexaboutno aff

Bibliographic record

VenueDIGITAL.CSIC (Spanish National Research Council (CSIC)) · 2018
Typearticle
Languagees
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsSpanish Civil WarPower (physics)EnlightenmentBiopowerPopular culture
DOInot available

Abstract

fetched live from OpenAlex

Vídeo del Panel 4 del "Congreso Internacional. Cuerpos incómodos: Violencia masiva, fosas comunes y necropolítica”. Celebrado en Donostia en el marco de los cursos de verano de la Universidad del País Vasco los días 18-21 de julio de 2008. El panel 4 incluye las siguientes conferencias: Ulrike Capdepón (moderadora); María García Alonso (UNED): El poder de los huesos. Usos religiosos y profanos de las reliquias de la guerra civil española / The Power of Bones: Religious and Profane Uses of Spanish Civil War relics. Miriam Saqqa (CSIC): Investigando la biopolítica del franquismo. Del cadáver al archivo / Investigating the Biopolitics of Francoism: From the Corpse to the Archive. Marije Hristova (CSIC) y Monika Zychlinska (U Warsaw): Łączka in a Jar: Devotion and Sacralization in Mass Grave Exhumations of the Cursed Soldiers in Poland / Łączka en un frasco. Devoción y sacralización en las exhumaciones de fosas comunes de los soldados malditos en Polonia. Germán Labrador (U de Princeton): La memoria y la piedra. La represión franquista y el arte popular en la Galicia de posguerra / The Memory and the Stone: Francoist Repression y Popular Art In Postwar Galicia.

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)0.009
metaresearch head score (Gemma)0.055
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.866
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.055
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0020.003
Scholarly communication0.0020.002
Open science0.0040.002
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 head0.131
GPT teacher head0.334
Teacher spread0.203 · 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 designTheoretical or conceptual
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

Explore more

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