Wikimedia Australia and first nations metadata: utilising the ATSILIRN protocols to create culturally appropriate description and access
Bibliographic record
Abstract
Protocols have been utilised as a tool to build dialogue on the management of Indigenous knowledges in a library and archive context. This paper discusses how the Aboriginal and Torres Strait Islander Protocols for Libraries, Archives and Information Services (ATSILIRN [n.d.] Protocols for Libraries Archives and Information Services. http://atsilirn.aiatsis.gov.au/protocols.php) could guide Wikimedia projects and Wikipedia and Wikidata editors to better describe Aboriginal and Torres Strait Islander content in a self-determined and culturally appropriate manner. Focussing specifically on questions of Description and Classification (Protocol 5), the paper examines the limitations of current metadata and Wikipedia practices and opportunities for embedding and being led by Aboriginal and Torres Strait Islander worldviews and principles. Overall, the article contributes to further understanding the challenges and opportunities of including Indigenous knowledges and perspectives in open access platforms.
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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 | 0.035 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.011 | 0.020 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".