Local government alternative dispute resolution: a British Columbian case study
Bibliographic record
Abstract
This research undertook a case study of the intergovernmental Alternative Dispute Resolution (ADR) process administered by the Ministry of Community Development (MCD) in the province of British Columbia (BC), Canada. This study used concurrent nested mixed research methods in order to discover how best to deliver, monitor, measure, and communicate MCD’s ADR process. The dominant research approach used was qualitative and involved informal interviews and document analysis. The purpose of the interview portion of the research was to flesh out descriptors and perceptions of MCD’s ADR process with the objective of coming to a greater understanding of current and potential delivery, monitoring, measurement, and communication mechanisms most appropriate for the ADR process. The interviews undertaken in this research also provide the opportunity for MCD staff to deliver feedback on, and offer insights into, the research. The document analysis portion of the research involved a textual analysis of MCD’s electronic and print ADR process communications in order to build on the descriptors and perceptions identified in the interviews, providing for a more full understanding of the ADR process and the delivery, monitoring, measuring, and communication strategies best suited to it. The nested quantitative portion of the research involved the use of secondary, anonymized data garnered from a survey prepared by MCD’s Director of Intergovernmental Relations which has been in distribution for a number of years. The survey used a Likert scale to measure process indicators. Data from this survey was analyzed to generate information about how participant respondents in the ADR process perceived certain attributes of the ADR services. Potential implications of this research include: providing applied tools to monitor, measure, and communicate ADR processes, increasing accountability in government administered publicly funded programs, generating ideas around local government ADR processes, improving dispute management in increasingly complex intergovernmental relational contexts, and addressing the literature gap on ADR processes and intergovernmental relations. The general findings of this research included clarification of MCD’s ADR process mission, vision, and goals, its communication strategy, and the perspectives of facilitators on both successful and challenging aspects of process delivery. The research findings also identified gaps in process performance monitoring and measurement and discussed the implications of MCD’s ADR process survey data results. This thesis concludes with recommendations to update process mission, vision, and goals. The thesis also suggests further ways to monitor and communicate MCD’s ADR process and provides templates for doing so. Finally, this thesis identifies opportunities to strengthen practices in process delivery. In the final chapter, areas for future research are suggested including: • ADR program evaluations generally, • Provincially administered inter-local government ADR processes, • Comparative work on inter-local government ADR in other national jurisdictions, • Ways to incorporate diverse methods and cultural approaches to conflicts and disputes into inter-local government ADR processes, • Studies into BC local government perspectives on MCD’s ADR process, and • Ways in which BC First Nations governments could be included in inter-local government ADR processes.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.009 |
| Science and technology studies | 0.037 | 0.006 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".