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Record W2314346884 · doi:10.1177/0971721813484381

Producing ‘Human Elements Based Medical Technologies’ in Biotech Companies: Some Ethical and Organisational Ingredients for Innovative Cooking

2013· article· en· W2314346884 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience Technology and Society · 2013
Typearticle
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsBioethicsJudgementEngineering ethicsBusinessBiotechnologySociologyPolitical scienceEngineeringLawBiology

Abstract

fetched live from OpenAlex

This article is based on the findings of an EU-funded qualitative research project, entitled ‘From GMP to GBP: Fostering good bioethics practices [GBP] among the European biotechnology industry’, which seeks to improve the understanding of bioethical issues through the observation of the daily practices in European biotechnology companies and proposes a methodology approaching ethical issues. The comparative study was carried out in biotech companies in France, Italy, Sweden, Hungary and Belgium which develop a wide range of new technologies, all of them involving human materials or where human subjects participate (in clinical trials). Based on our findings in these local settings, we suggest that the notion of bioethics and the way its production is theorised need to be re-conceptualised. We argue that material practices and moral statements are intermingled in inextricable ways that render the formation of bioethical concerns fully dependent on the organisational landscape in which it is embedded. More precisely, the here presented co-production model of moral statements and organisational practices presents a set of common factors that influence how bioethical discourses are shaped, despite the heterogeneity of their epistemic cultures. For example, the procedural design of cell-based-products, the modes of collecting and storing biological specimen, the relationship between patients and companies and technological transfers to emerging countries are defining components that contribute to the shaping process of bioethical concerns. Thus, the path dependency of bioethical concerns relies on an already existing, specific infrastructure and existing relationships within and outside a company rather than on external judgement subsequently applied to its objects, or a collection of processes of reasoning coming from external institutions.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.009
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.022
GPT teacher head0.336
Teacher spread0.314 · 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