Exploring the Roots of the Environmental Crisis: Opportunity for Social Transformation
Bibliographic record
Abstract
The environmental crisis is the canary in the mineshaft of modern society. Miners, in previous generations, checked the quality of air in a mine by lowering a canary in a cage into a mineshaft. If the canary came back up alive the miners would go into the mine; if the canary came back dead the miners would not proceed as the mine was dangerous and unsafe. The environmental crisis is playing a similar role for people in modern society. For example, plants and animals are becoming extinct in unprecedented numbers, the oceans’ fisheries are in decline, water is increasingly polluted, and even the air we breathe - so called ‘fresh air’ - is frequently smog (air contaminated by industrial and agricultural pollutants). Further, industrial processes have released toxins upon Earth which have altered the environment so severely that the reproductive capabilities of animals (including the human) are affected (see for example Colborn, Dumanoski and Myers, 1999). These events are informing us in quite clear terms that the generativity of Earth and the social structures dependent upon it are in peril. Through the environmental crisis the Earth is reacting to human behaviour and is warning us - perhaps beseeching us - to respond.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.020 | 0.053 |
| Scholarly communication | 0.017 | 0.021 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.014 | 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".