The Anthropocene Obscene: Poetic inquiry and evocative evidence of inequality
Bibliographic record
Abstract
Abstract Poetic inquiry is used to highlight contrasting lived experiences of vulnerability and worsening socio‐ecological outcomes among Australia's fastest growing coastal communities. Our approach interweaves multiple participant voices across local and national scales to juxtapose the contrasts of inequality, enmesh social and ecological experiences, and ask reflexive questions of audiences. We offer an evocative portrayal of inequality to the growing body of work demonstrating that unequal and intensifying vulnerabilities are created and sustained through complicated, non‐adaptive and hierarchical social systems. We demonstrate that poetic inquiry can interrogate complex system phenomena and broad concepts, such as the Anthropocene, to distil critical and systemic issues while retaining undeniable connections with the deeply personal implications of socio‐ecological change. Hence, poetic inquiry can serve analytical and descriptive purposes towards an emotional and political aesthetic providing a compelling reorientation from more conventional modes of inquiry and representation. In this study, the misuse of power and privilege in the Anthropocene is reduced and revealed as the Obscene.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.015 | 0.082 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".