A class analytic approach to the Gezi Park events: Challenging the ‘middle class’ myth
Bibliographic record
Abstract
On 31 May 2013, what began as a localised demonstration against the demolition of a public park in Istanbul escalated into anti-government protests of unprecedented form and scale in Turkey’s modern history. The class configuration of the Gezi Park events occupied the forefront of discussions within and outside the Turkish left. Mainstream accounts branded the events as an uprising of ‘middle classes’ concerned almost exclusively with secularism. Drawing on a Poulantzasian/Wrightian framework, we argue that the Gezi Park events can be reduced neither to a middle-class nor a secularism-centered uprising. They represent, instead, an initiative of various wage-earning class fractions led by service-sector employees and the educated youth, which rests on socioeconomic grievances of proletarianisation under neoliberalism.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.018 | 0.030 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".