Collaboration in public services : the challenge for evaluation
Bibliographic record
Abstract
The International Group for Policy and Program Evaluation (INTEVAL) serves as a forum for scholars and practitioners of public policy to discuss ideas and developments as a community dedicated to enhancing the contribution of evaluation to government. From the group's studies has emerged a concern with the impact of public management reforms. Collaboration in Public Services examines collaboration in the delivery of public policies and identifies the challenges for policy and program evaluation. Written by a mix of academics, program managers, evaluators, and auditors, this volume explores the forms and challenges of collaboration in different national contexts. Chapter 1 introduces the notion and manifestations of collaboration and discusses emerging issues. Chapter 2 examines partnerships and networks of public service delivery. Chapter 3, drawing on Dutch and British data, reveals the QUANGO as both a collaborative end and means. Chapter 4 analyzes Israel's push to enhance collaboration with voluntary organizations. Chapter 5 examines the Canadian and Danish experiences. Chapter 6 suggests that the creation of markets to improve quality has not been totally successful at least in Nordic countries. Chapter 7 suggests that traditional service values such as trust and parliamentary accountability are challenged by the complexity of collaboration, but, using illustrations from Canada and other OECD countries, argues that results-based governance can increase trust, flexibility, and empowerment. Chapter 8 demonstrates from Dutch and Canadian experiences that auditor responses to collaborative delivery tend to overlook traditional roles as guardians of accountability on behalf of parliaments. Chapter 9 deliberates the efficacy of programs involving multiple partners. Chapter 10 discusses the lessons and challenges of evaluation and collaborative government.
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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 | 0.568 | 0.526 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.012 | 0.016 |
| Science and technology studies | 0.020 | 0.076 |
| Scholarly communication | 0.063 | 0.081 |
| Open science | 0.008 | 0.047 |
| Research integrity | 0.021 | 0.027 |
| Insufficient payload (model declined to judge) | 0.005 | 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".