Negotiating Ecological Intersectionality: Environmental Calamity, Sustainability and EcoArtt
Bibliographic record
Abstract
Negotiating Ecological Intersectionality: Illuminating Environmental Calamity and Sustainability through EcoArt: As ecological crises accelerate, the interconnectedness of climate change with human societies and the need for environmental sustainability increasingly requires investigation and illumination, particularly through intersectional methodologies and their application to art. These intersectional methodologies may be defined as exposing, following K. Davis, “the interaction between gender, race and other categories of difference in individual lives, social practices, institutional arrangements, and cultural ideologies and the outcomes of these interactions in terms of power”. How diverse genders, sexualities and ethnicities relate differently to climate change, due to their specific situatedness in power structures, institutional practices, social categorisations and knowledge production, has been exposed through multileveled intersectional investigations and illuminated through EcoArt, including Ecophotography. EcoArtists have endeavoured to reveal how power structures, categorisations and unsustainable lifestyles have contributed to the emission of greenhouse gases, global warming and ecological crises while challenging and renegotiating them in order to explore how climate change may be combated and environmental sustainability pursued. By focusing upon the Ecophotography of the Canadian, Edward Burtynsky and Bangladeshean, Munem Wasif, plus the EcoArt of English, Michael Pinsky and Australian, Janet Laurence, this presentation shall explore their diverse engagements with ecological intersectionality. After focusing upon their exposures of the impact of diverse ecological disasters, particularly in relation to new planetary awareness of environmental risks and sustainability, this presentation shall then examine how these EcoArtists also explore ways in which relations between human subjects and the global environmental imaginary may be reconceived in time and space.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.057 |
| Scholarly communication | 0.020 | 0.017 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 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".