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Record W2587233229 · doi:10.7202/1038682ar

Science, Translation and the Mangle: A Performative Conceptualization of Scientific Translation

2017· article· en· W2587233229 on OpenAlexvenueno aff
Maeve Olohan

Bibliographic record

VenueMeta Journal des traducteurs · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsPerformative utteranceEpistemologySociologyAgency (philosophy)Translation studiesSituatedConceptualizationEngineering ethicsSocial scienceEngineeringComputer sciencePhilosophyLinguisticsArtificial intelligence

Abstract

fetched live from OpenAlex

Against a backdrop of growing interest in historical and sociological approaches to the translation of science, this paper explores the conceptual potential of Andrew Pickering’s ‘mangle of practice’ (Pickering 1992; 1993; 1995; Pickering and Guzik 2008) as a sociological framework for research into the translation of science. Pickering’s approach is situated within a performative idiom of science and seeks to account for the interplay of material and human agency in scientific practice. It sees scientific and technological advances as emerging temporally from a dialectic of resistance and accommodation, metaphorically the mangle of practice. This paper introduces the main tenets of Pickering’s argument, contextualizing it within the field of science and technology studies. It then explores some of the implications of construing translation in these terms. Firstly, this conceptual approach helps to recognize the role of translation in the performance of science and to seek ways of studying translation practices as an integral component of scientific practices. Secondly, Pickering’s posthumanist or decentred perspective focuses on both material and human agency and the interplay between them; a similar approach to the study of translation would foreground the interaction between translator agency and material performativity in studies of translation practices. I conclude with proposals for adopting this ontological shift in translation studies, where it may have the potential to enhance our understanding of translation practices, in particular in relation to tools, technologies and sociotechnical developments in translation.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.937
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.007
Scholarly communication0.0020.003
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.142
GPT teacher head0.311
Teacher spread0.169 · 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 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

Citations10
Published2017
Admission routes1
Has abstractyes

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