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Record W4380089811 · doi:10.1093/jiplp/jpad052

Patenting human biological materials and data: balancing the reward of innovation with the <i>ordre public</i> and morality exception

2023· article· en· W4380089811 on OpenAlex
Esra Demir, Evert Stamhuis

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

VenueJournal of Intellectual Property Law & Practice · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsMoralityPsychologyBusinessPolitical scienceLaw

Abstract

fetched live from OpenAlex

The availability of human biological materials and data plays a key role in promoting biotechnological innovations and conducting biomedical research.While the function of patent rights in promoting innovation is widely discussed, there are still overarching concerns in patenting human biological materials and data, including triggering commercialization and commodification of the human body, precluding affordable access to the products or services and inducing interest extraction by patent holders to recoup investments and make excessive profits.• This article aims to analyse the extent to which the ordre public and morality exclusion can protect the human being whose bodily material has been taken and prevent legal and ethical exploitation.• We argue that the concept of ordre public and morality needs to be modified, sparking a new governance approach to better protecting human beings in a patent system that is more participatory, accountable and transparent in patent assessment.materials and technologies have a wide range of applications in biomedicine today, such as next-generation

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)0.006
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score0.771

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0000.001
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 head0.281
GPT teacher head0.304
Teacher spread0.023 · 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