Bibliographic record
Abstract
What I am going to discuss are certain relations between culture and the global process of increasing ecological unsustainability. One of the many factors which make it difficult to change the process into one of decreasing unsustainability is the shift in ways of thinking from that of ecology to that of environment. The latter term suggests that we have to do with something outside humanity, something we regrettably are dependent upon. It is easier to mobilize people and money if we acknowledge human tendency to self-destruction through policies which not only spoil our nests, but leads us away from our own basic goals in life, whether it is called happiness or not. The increasing ecological unsustainability is something much nearer to our souls and selves than we have traditionally assumed. It is today often acknowledged that overcoming the increasing ecological crisis—the still increasing level of ecological unsustainability—leads invariably to problems in the humanities, in sociology and political science. It even fosters new branches like environmental diplomacy. The Canadian government decided to propose to stop complaining harshly about air pollution in Canada due to US pollutants provided the government of the US agreed to a trade treaty favorable to Canada. It is today accepted that every major ecological problem has a social and political aspect. Furthermore, it is clear that technological invention, even of a revolutionary kind since the 1960s, such as solar energy, had practically no influence on the curve of
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".