CONTROL PATTERNS IN CONTRACTING‐OUT RELATIONSHIPS: IT MATTERS WHAT YOU DO, NOT WHO YOU ARE
Bibliographic record
Abstract
The contracting‐out of public services has often been accompanied by a strong academic focus on the emergence of new governance forms, and a general neglect of the processes and practices through which contracted‐out services are controlled and monitored. To fill this gap, we draw on contracting‐out and inter‐organizational control literatures to explore the adoption of control mechanisms for public service provision at the municipal level and the variables that can explain their choice. Our results, based on a survey of Italian municipalities, show that in the presence of contracting‐out, market‐, hierarchy‐, and trust‐based controls display different intensities, can coexist, and are explained by different variables. Service characteristics are more effective in explaining market‐ and hierarchy‐based controls than relationship characteristics. Trust‐based controls are the most widespread, but cannot be explained by the variables traditionally identified in contracting‐out and inter‐organizational control studies.
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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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".