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(BIO)Technological Images about Human Self-construction on Spain Context: A Preliminar Study

2010· article· en· W3124492422 on OpenAlexvenueno aff
Juan R. Coca, Jesús A. Valero Matas

Bibliographic record

VenueStudies in sociology of science · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicLiterary and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMetaphorContext (archaeology)SociologyOrder (exchange)Social scienceHistoryPhilosophyBusinessArchaeology

Abstract

fetched live from OpenAlex

The study of (bio) technology has a great social significance. As time goes by, the human being is getting more linked to technology. (Bio)technology and society are, therefore, two inseparable fields. Furthermore, this study shows the importance of setting a new context of analysis for (bio)technology. This context will be a polycontexture formed by biological, technical, psychological, sociological and axiological factors. In order to analyze this polycontexture, we consider that one of the most powerful methods is that used by social imageries. Social imageries have been studied by many researchers, but we believe that Juan Luis Pintos has developed the best method. In the end, this paper concludes that the materialization of this polycontexture is the cyborg metaphor. Keywords: Cyborg; Policontexture; Juan Luis Pintos; Socials Imageries

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.009
Scholarly communication0.0040.003
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.045
GPT teacher head0.384
Teacher spread0.339 · 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.

Study designQualitative
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
Published2010
Admission routes1
Has abstractyes

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