Preventing indigenous elements from being registered as trademarks: a comparison of approaches across countries
Bibliographic record
Abstract
Three representative countries (Canada, the United States and New Zealand) have adopted different models to provide defensive trademark protection for indigenous cultural elements. Under the trademark defensive protection system, provisions such as the ‘offence clause’ or ‘misleading public clause’ can be utilized to prevent others from incorporating indigenous elements into their trademarks. In New Zealand, the offence clause primarily serves to prevent trademarks from offending the Māori culture. After the US Supreme Court ruled that offensive clause (disparagement clause) was unconstitutional, the USPTO can use ‘misleading public clauses’ to prevent others from registering indigenous official insignia. Taiwan uses both of these clauses. Based on Taiwan’s experience, it has been observed that the misleading public clause can offer more extensive protection compared to the offence clause. It has become an important tool in preventing the registration of indigenous cultural elements as trademarks. However, defensive protection does have its limitations. In particular, invalidating a trademark that has been registered for many years can be controversial. The invocation of the ‘misleading public clause’ may allow a broader range of parties to initiate cancellation proceedings compared to the ‘offence clause’ and is less susceptible to the issue of laches (delay in exercising rights). Even the ‘misleading public clause’ can be used as grounds for revocation, subject to fewer restrictions.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".