Bibliographic record
Abstract
Research Background: Carol McGregor’s Skin Country (2018) is an oversized possum skin cloak intertwined with burnt and painted illustrations using ochres and charcoal. Depicting an integrated map of native plants used across Greater Brisbane Aboriginal communities each skin has been intricately hand sewn together to create a canvas of the Brisbane River and its journey to the mountains, bay, and coastlines. The immersive scale of the cloak emphasises the wide-spread extent of local flora utilised by Aboriginal people. Inspired by Bruce Pascoe’s significant book Dark Emu: Black Seeds: agriculture or accident? (2014) which reveals a long history of Aboriginal agriculture previously omitted from Australian history, Skin Country also celebrates the power of traditional wisdom, strong living culture, and the vitality of the land. Research Contribution: Throughout the development of Skin Country, McGregor worked with Traditional Owners, Brisbane Elders, and community members to collectively share stories and memories of plant uses and histories. Encompassing intimate reflection of knowledge systems relating to the natural environment and skills of creation. Following Indigenous protocols integral to McGregor’s practice, she shares the diverse traditional applications of plants by Aboriginal people and bringing this knowledge into discussion through cloak making. Research Significance: Skin Country was commission by the Institute of Modern Art with the support of the Australia Council of the Arts and exhibited in The Commute, Institute of Modern Art, Brisbane, 2018 with visiting Indigenous curator Freja Carmichael (Quandamooka). Re-exhibited in transits and returns, Vancouver Art Gallery, Canada, 2019 and Art of the Skins: un-silencing and remembering, Griffith University, 2019. In 2020 was acquired by Queensland Art Gallery | Gallery of Modern Art (QAGoMA), Brisbane.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.456 | 0.216 |
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".