When Local Class Unionism Meets International Solidarity: A Case of Union Revitalisation in Turkey
Bibliographic record
Abstract
The article concerns the recent transformation and ensuing successes of a Turkish trade union of road transport workers called Tüm Taşıma İşçileri Sendikası (TÜMTİS). In the mid-2000s, TÜMTİS was mainly organised in small-sized freight companies having around 1 500 members with collective contracts. The strategic choice of a new leadership to concentrate on a large-scale, international firm with the support of Global Unions was the turning point. The ensuing United Parcel Service campaign ended with a collective agreement for nearly 2 700 new members in 2011. The union won its second large-scale organising victory at DHL in 2014. At the time of writing, a third large-scale firm is on the verge of recognition. To scrutinise this case, I use the power resources approach in a critical way. To the approach, I add an examination of the subjectivities of union leaders by drawing on the debates about different types of unionisms, importance of the ideology and motivations. I argue that the agency behind this revitalisation can be only explained by taking both its objectivities and subjectivities into account. While the class unionism embraced by TÜMTİS leaders explains the subjective side of the story, associational power from below and its meeting with international solidarity play the key role on the objective side.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.022 | 0.015 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".