Aesthetic Consolation: A Possible Remedy for Solastalgia in James Bradley’s Clade (2017)
Bibliographic record
Abstract
Climate change is one of the significant and threatening problems worldwide. It has attracted the attention of scientists and politicians as well as writers and critics especially in the western world. Writers have responded by writing climate change fiction despite the challenges of representation. James Bradley, an Australian novelist and critic, is one of those writers who are deeply occupied by the impacts of climate change. He has written Clade (2017) which traces the life of Adam Leith, a climatologist, and his family descendants amid the disastrous consequences of climate change. To analyze this novel, the researcher focuses on solastalgia, and applies the approach of everyday aesthetics. In a nutshell, the paper attempts to highlight the impact of climate change, examine the relationship between the characters and their environment, and explore the possibility of adaptation and detection of aesthetic values in an environment destroyed by climate change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".