Children of their city: migration, resistance, and the construction of a working-class identity in late nineteenth-century Stockholm
Bibliographic record
Abstract
Formidable economic and social forces shaped the lives of working-class men and women in Stockholm at the end of the nineteenth century as they confronted difficulty in securing consistent work and faced high food and housing costs as well as class-based prejudice in the popular press. These people responded with unique expressions of self-determination and demonstrated a profound resilience in the form of subtle, mundane, and nearly imperceptible acts of resistance. These are revealed in an examination of their daily lives and struggles and situating their experiences within the overall creation of a working-class identity. E. P. Thompson’s definition of “class” offers a starting point to understanding the creation of this identity as do post-structural approaches that examine the language used to describe these men and women. Here “class” refers to fluid boundaries delineated more by common experiences and behaviours rather than social standing or occupation. An ephemeral lure of bright lights and a promising future continued to draw men and women to the city. Biographies of three men and three women who moved from Kalmar County to Stockholm in the 1880s reveal the migration histories and the tactics and strategies they and thousands of others employed to try and survive after they arrived. They and their fellow workers responded to efforts to control them and their behaviour. Some men resorted to drinking as a form of resistance while women forced to resort to prostitution devised their own tactics to avoid police scrutiny and compulsory medical examinations. Men and women of the working class converged within the space of the tavern. It served as the most important locus of socialisation and networking for many men although women’s presence there has been understated but they were integral to the tavern after the passage of the Gothenburg System that required much more stringent scrutiny to cut down on public drunkenness. Workers fought back against this attempt to subdue one of the most important institutions in their lives by re-appropriating this space and using it to construct social networks that transcended occupational and geographic and served as the basis for a working-class identity.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.018 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".