Bibliographic record
Abstract
Coalmining was a notoriously dangerous industry and many of its workers experienced injury and disease. However, the experiences of the many disabled people within Britain’s most dangerous industry have gone largely unrecognised by historians. This book examines the British coal industry through the lens of disability, using an interdisciplinary approach to examine the lives of disabled miners and their families.The book considers the coal industry at a time when it was one of Britain’s most important industries, and follows it through a period of growth up to the First World War, through strikes, depression and wartime, and into an era of decline. During this time, the statutory provision for disabled people changed considerably, most notably with the first programme of state compensation for workplace injury. And yet disabled people remained a constant presence in the industry as many disabled miners continued their jobs or took up ‘light work’. The burgeoning coalfields literature used images of disability on a frequent basis and disabled characters were used to represent the human toll of the industry.A diverse range of sources are used to examine the economic, social, political and cultural impact of disability in the coal industry, looking beyond formal coal company and union records to include autobiographies, novels and oral testimony. It argues that, far from being excluded entirely from British industry, disability and disabled people were central to its development. The book will appeal to students and academics interested in disability history, disability studies, social and cultural history, and representations of disability in literature.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.017 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.558 | 0.489 |
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".