Introduction. Postindustrial natures: Hyper‐mobility and place‐attachments
Bibliographic record
Abstract
[EN] The current globalization of the world is resulting on entire regions suffering sudden structural reconfigurations through the re-organization of economic activities of industrial towns and agrarian landscapes. Contemporary Western societies have seen industries and its associated values move away to cheaper locales, replaced by a services economy focused on providing leisure to these urban dominated societies. Postindustrial landscapes, characterized by economic decay, depopulation, and abandonment, followed by reinvestment, resettlement, and rejuvenation, are not unique to the last century. But what marks out the last thirty years of the twentieth century is the technological revolution in travel and communication, accompanied by the rise of modern environmentalisms. This introduction and the essays that it prefaces are taking forward a growing debate on how to re-theorize the concept of social nature, by reflecting upon it under the specific light of postindustrial social formations. They look at how nature is imagined and pursued as an aesthetic, a moral compass, and as diverse locations inside and outside the cultural and material separations already made in the social construction of industrial space. The emergence of distinct postindustrial social imaginaries, where divisions like folk and rational thought are not only questioned but also newly remade, is of particular interest to this collection of essays.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".