Connecting neighborhoods with worksites: coercion, labor migration, and shipbuilding workers in late Ottoman İstanbul
Bibliographic record
Abstract
Abstract This article highlights the state’s labor coercion practices and their perpetual characteristic in defining the history of migration and migrants’ experiences in the city. It underlines the internal relationship between production processes and relations on the one hand and the mobility of workers and their families on the other. For this purpose, it focuses on the migration dynamics of shipbuilding workers in mid-nineteenth-century İstanbul, most of whom worked in the Imperial Arsenal ( Tersane-i Amire ) and dwelled in the neighborhoods of the surrounding quarter of Kasımpaşa. I will utilize the population records of one of these neighborhoods, the Seyyid Ali Çelebi, where the relationship between the worksite and the residential community was evident, and the wage records of the Imperial Arsenal to understand the relationality of migration and work processes. Based on an analysis of these sources, I will point to the connections between the configuration of migration networks built in or through the Arsenal and the settlement patterns in the neighborhood. I will particularly argue that relations at the workplace and the coercive dynamics that underlined these relations significantly impacted the migration and settlement patterns in the nineteenth century.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".