The Personality of Environmental Prediction: Griffith Taylor as 'Latter-day Prophet'
Bibliographic record
Abstract
Environmental prediction is a practice that may establish and enhance the status of predictors but it also carries risks that vary in relation to the professional and political contexts of its communication. Exploring the lives of scientists involved in the difficult task of environmental prediction highlights the significance of personal identities in the cultural history of science. Geographer Griffith Taylor (1880–1963), whose raison d'être was environmental prediction, is an ideal subject to examine from this perspective. Facing opposition to his early predictions of Australia's limited settlement prospects, owing to the continent's aridity, he used intemperate language to deliver sober warnings and sparred with naysayers and doubters in the popular media. By the 1920s he saw himself as a ‘latter-day prophet', and he carried that sense of self forward when he moved to North America in 1928. Yet in Canada his environmental predictions, although favourable, were considered overly optimistic and often disregarded altogether. This prophet realized that he was happier being attacked than ignored. Taylor's career suggests that positive prognostication, when dismissed, offers less personal compensation than cautionary prophesies that face opposition in hostile political or intellectual contexts.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.025 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.002 | 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".