Governance in public procurement: the reform of Turkey’s public procurement system
Bibliographic record
Abstract
Regulation and control of public procurement constitute a crucial field for the application of governance ideals and practices. This study explores the public procurement reform process in Turkey with reference to the implementation of governance as part of an ongoing neoliberal discourse and practice. Turkey’s public procurement system was reformed in 2002 in line with governance principles of transparency, anti-corruption, securing competition and by establishing an independent regulatory institution. A decade after this reform, our analysis shows that political will, economic forces in the procurement market and problems in the institutional-organizational setting are factors that play a role in the relapses from governance ideals and practices. Points for practitioners Reforms aimed at achieving good governance in public procurements are hard to sustain. The specific institutional traditions of local contexts, interventions of political authorities and powerful economic interests play an important role in the success of reforms. Persistent ad hoc modifications of public procurement laws erode the regulatory scope, change the composition and political autonomy of board membership, and undermine the principles of transparency, accountability and competitiveness. There is a need to actively ensure sustainability of governance principles through strong defense mechanisms which should be institutionalized within local social dynamics.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".