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Record W4388723364 · doi:10.5944/rif.19.2022.34422

Machenschaft, vivencias y temporalidad. Historia, aceleración y crítica de la Modernidad en Heidegger (1936-1944)

2022· article· es· W4388723364 on OpenAlexaff
César Gómez Algarra

Bibliographic record

VenueInvestigaciones Fenomenológicas · 2022
Typearticle
Languagees
FieldPsychology
TopicPhenomenology and Existential Philosophy
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesPhilosophyLogos Bible SoftwareArtTheology

Abstract

fetched live from OpenAlex

Los convulsos acontecimientos de estos últimos años han demostrado, a escala global, cuán enajenante es nuestra experiencia presente del tiempo. Las tendencias actuales de la teoría crítica y otros enfoques histórico-sociológicos insisten en el ritmo devorador de la aceleración (P. Virilio; H. Rosa) y en la reconfiguración temporal a partir del “presentismo” (Koselleck; F. Hartog). Sin embargo, sabemos que estas cuestiones distan de ser absolutamente nuevas, y que ya preocupaban a los filósofos y a los fenomenólogos en la primera mitad del siglo XX. La publicación reciente de los últimos tratados del Ereignis y de los Cuadernos negros, redactados en los años 1930 y 1940, nos permite acceder a una reflexión original sobre lo que Heidegger nombra la maquinación o fabricación [Machenschaft]. Nos gustaría analizar la manera en la que, a partir de la fabricación, se puede replantear el sentido de nuestra experiencia temporal íntima frente a la situación moderna. Más concretamente, ahondaremos en las formas en las que la primacía de la fabricación funciona como cerrazón de posibilidades, llegando a impedir que pueda ocurrir algo realmente “histórico”.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
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 score0.041
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.026
Scholarly communication0.0050.004
Open science0.0000.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.318
Teacher spread0.297 · 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 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
Published2022
Admission routes1
Has abstractyes

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