Life among the Ruins: Deindustrialization in Historiographical Perspective
Bibliographic record
Abstract
I live in a depleted city (Sydney), in a deindustrialized region (Cape Breton Regional Municipality), on a marginal island (Cape Breton), in a have-not province (Nova Scotia). As recently as the mid-1960s, the city, region, and island were supported economically by coal mining, steel making, and fish processing; thousands were employed directly in these areas, while thousands upon thousands more provided supportive goods and services. Things have changed dramatically since then. No one on the island goes underground for coal anymore, nor does anyone here smelt iron ore. Fish plant workers remain, but they are few in number and endangered. Within the Cape Breton Regional Municipality, which used to be called “industrial Cape Breton” because the island’s steel industry and nearly all of its coal mines fell within its boundaries, the impact of this protracted economic decline has been dramatic and seemingly irreversible. Between 1961 and 2011, the municipality’s population has contracted from 131,507 to 97,398, a drop of nearly 26 per cent; immigration to the region is non-existent. The average family income is 40 per cent less than in the rest of Canada; 24 per cent of children under the age of six live in low-income houses, a rate above the provincial and national average; most of those households are led by single women. Levels of arthritis, diabetes, obesity, high blood pressure, substance abuse, and cancer are either among the highest or (in the case of cancer) are the highest in the country. Derelict houses and buildings line many streets, and arson is all too common. The municipal government is practically bankrupt, while property taxes are the highest in the province.1 The (official) unemployment rate for the island as a whole hovers
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.012 | 0.026 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".