Examining participatory governance in a devolving UK: Insights from national parks policy development in Northern Ireland
Bibliographic record
Abstract
This paper provides a contemporary examination of policy making and participatory practice in the context of devolving governance in the UK. The paper takes Northern Ireland as its focus and is particularly timely considering the context of devolved governance, the ongoing transition from conflict to relative peace and the potential for rejuvenating democracy through participatory governance. The paper concentrates on one particular policy process, namely the attempted designation of a national park in the Mournes Area of Outstanding Natural Beauty. A thematic analysis of qualitative data is drawn upon to analyse the structural factors that framed the policy-making process, in particular the role of power in determining how consultation processes were initiated, designed and undertaken. Using Lukes’ model as an analytical framework, power is shown to manifest at multiple levels within the policy-making process to influence policy outcomes. The paper reveals how the persistence of a top-down approach to policy development combined with a highly parochial political outlook undermined attempts to designate a Mourne National Park. The paper concludes that, given the immaturity of recently devolved government in Northern Ireland, in this instance, the democratising intentions of devolved governance have not been met. This has implications for Northern Ireland’s recent reform of public administration which devolves certain planning powers to local authority level and the management of the internationally significant Mournes landscape.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.013 | 0.021 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".