ENDÜSTRİ ÖZNELERİNİN ÇALIŞMA, YAŞAM VE KOLLEKTİVİTE MEKANLARINDA OLUŞUMU: ESKİŞEHİR 1923-1980
Bibliographic record
Abstract
State-based industry in Eskişehir was introduced by state-owned factories in the second quarter of the twentieth century. Accordingly, three large-scale industries, the railway factory, the sugar factory, and the Sümerbank print factory, were founded or developed by the Turkish state. In line with these developments, the city began to be transformed through industrialization, migration, and urbanization. Between 1950 and 1980, the industrial workers in Eskişehir began to find their own voices and took part in intense organizational debates within the workers’ organizations: trade unions, editorial rooms, consumer cooperatives, and holiday camps. Thus, many industrial workers spread to the larger urban environment, searching for living and collective spaces, struggling to form organizations as organized industrial subjects, and interacting with the social and cultural life of the city. In addition to what the state introduced, this dissertation discusses how the industrial employees produced in and interacted with the urban environment by covering all employees working in the factory - managers, officials, engineers, workers and other employees - to explore a more diverse network of actors. The main objective is to understand how work, living, and collective spaces were produced and used resulting in multiple industrial subjects alongside an analysis of how this built environment was positioned within social, economic, and political change in the city.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".