Crossing boundaries in public management and policy : the international experience
Bibliographic record
Abstract
Part I: Introduction and the Fundamental Questions 1. Crossing Boundaries in Public Management and Policy: An Introduction (Janine O'Flynn) 2. Crossing Boundaries: The Fundamental Questions in Public Management and Policy (Janine O'Flynn) Part II: Solutions to Cross-Boundary Dilemmas? 3. The Cross-Organization Collaboration Solution?: Conditions, Roles and Dynamics in New Zealand (Elizabeth Eppel, Derek Gill, Miriam Lips and Bill Ryan) 4. The Boundary Spanning Solution?: Crossing Boundaries in the United States (Kelly LeRoux) 5. The Culture Solution?: Culture and Common Purpose in Australia (Fiona Buick) 6. The Structure Solution?: Public Sector Mergers in the United Kingdom (Carole Talbot and Colin Talbot) 7. The People and Structure Solution?: Collegial Administration in Norway (Dag Arne Christensen, Tom Christensen, Per Laegreid and Tor Midtbo) 8. The Performance Target Solution?: Cross-Cutting Public Service Agreements in the United Kingdom (Akash Paun and Kate Blatchford) 9. The Collaboration Solution?: Factors for Collaborative Success (Brian Head) 10. The Soft Power Solution?: Managing without Authority (Owen Hughes) 11. The Diagnostic Solution?: Gauging Readiness for Cross-Boundary Working (Deborah Blackman) 12. The Responsiveness Solution?: Embedding Horizontal Governance in Canada (Evert A. Lindquist) Part III: Cases of Crossing Boundaries in Public Management and Policy 13. Children's Services: The Impact of Service Integration in England (Carole Talbot) 14. Education and Employment: Stumbling across Boundaries in the Netherlands (Esther Klaster) 15. Health: Overcoming Service Delivery Gaps in Austria (Sanja Korac and Iris Saliterer) 16. Community Safety: Partnerships across Boundaries in England (Joyce Liddle and John Diamond) 17. Airport Enclaves: Bridging Boundary Tensions between Airports and Cities (Timothy Donnet and Robyn Keast) Part IV: Conclusion 17. Crossing Boundaries in Public Management and Policy: Conclusion and Future Issues (Janine O'Flynn, Deborah Blackman and John Halligan)
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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 | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.010 |
| Science and technology studies | 0.017 | 0.020 |
| Scholarly communication | 0.023 | 0.023 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.013 | 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".