Making sense of the ruins: The historiography of deindustrialisation and its continued relevance in neoliberal times
Bibliographic record
Abstract
Abstract The political upheavals of recent years, including Brexit and the election of Donald Trump, have increased scholarly and public interest in the impact of deindustrialisation on working‐class communities. Building upon earlier literature reviews, this historiographical study examines the continued flowering of this interdisciplinary, transnational field of research. After briefly recounting the emergence of the field in response to the structural transformations of the 1970s and 80s, and its subsequent ‘cultural turn’, this review focuses on identifying the most promising strands of contemporary English‐language research. It notes the particularly innovative attempts to identify the ‘moral economy’ of deindustrialising societies, the growing study of the long‐term cultural legacies or ‘half‐life’ of deindustrialisation, and the renewed focus on the politics of memory and heritage preservation. Finally, it considers how scholars can constructively respond to the increasing public interest in deindustrialisation, challenge racialised and exclusionary definitions of the working‐class, and unpick the historical relationship between deindustrialisation and the social and political transformations of recent times.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.031 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".