Wandering footloose: Traditional knowledge and the “Public Domain” revisited
Bibliographic record
Abstract
Ongoing interdisciplinary theoretical interests over the “ownership of culture” is a complex conversation that has pitched traditional knowledge (TK) and its holders against other knowledge systems in a manner that implicates significant power relations and plural philosophical orientations over the governance of knowledge. Nowhere is the pressure on TK more pronounced than in the new‐found interest of the United States and its allies over the public domain, as evident in the work of the WIPO's special committee charged with negotiating sets of legal instruments for effective protection of TK, genetic resources, and folklore (a.ka. traditional cultural expressions). TK stakeholders are put on the defensive on the assumption that effective protection of TK would undermine the public domain. Ironically, led by the United States, countries who worked tirelessly over the decades to ratchet up intellectual property protection at the expense of the public domain have now reconstituted themselves into its later day champions when it comes to TK. However, it is not as if the Indigenous and local community custodians of TK have no approximation of the public domain in their customary laws, practices and dealings with knowledge production. There has yet to be an interest in non‐Eurocentric conceptions of the public domain. Such an interest presents an opportunity to revisit the public domain imperative in order to adumbrate an inclusive and multicultural jurisprudence of the phenomenon.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.017 | 0.101 |
| Scholarly communication | 0.029 | 0.043 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".