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Record W2214836276

Book Review: Law, Knowledge, Culture: The Production of Indigenous Knowledge in IP Law

2009· article· en· W2214836276 on OpenAlexaff
Chidi Oguamanam

Bibliographic record

VenueSSRN Electronic Journal · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicIndigenous Knowledge Systems and Agriculture
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsIntellectual propertyIndigenousLawCommoditizationPolitical scienceScholarshipTraditional knowledgeSociology
DOInot available

Abstract

fetched live from OpenAlex

Jane E. Anderson examines how diverse factors have shaped the negotiation of Indigenous knowledge (IK), especially in the evolution of Australian copyright. The emergence of claims to protect IK in an intellectual property framework are contextualized in the colonialist experience of exploitation. Part 1 gives a history of IP, showing that it is not a neutral area of law. IP related to IK is marked by the power relationship between Indigenous and settler peoples. The IP framework pigeonholes IK in an effort to maintain a facade of objectivity in a clearly subjective area of law. Part 2 discusses the politics of law, and the role of IP law in the commoditization of Aboriginal art/IK and co-optation of the cultural aspects of that art. Chapter six discusses case law regarding IK in IP, and underscores the judicial conservatism in challenging the rigid categories of IP law. Part three discusses culture as the only factor that differentiates IK within IP law. The author notes that appealing to culture in IP falsely assumes homogeneity of Indigenous peoples and perpetuates colonial bias and hegemony. The author gives a brief exploration of international instruments protecting IK, but fails to discuss the importance of the Convention on Biological Diversity for IK. The author concludes with a critique of the Australian national approach to IK. This is book is an interesting addition to the body of scholarship at the interface of IK and IP law. It is well-researched and well-written and would be resourceful for scholars from diverse disciplinary backgrounds.

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)0.002
metaresearch head score (Gemma)0.000
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: Review · Consensus signal: none
Teacher disagreement score0.821
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.225
Teacher spread0.218 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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
Published2009
Admission routes1
Has abstractyes

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