Advancing Pluralism in Impact Assessment Through Research Capacity: Lessons from the Yukon Territory, Canada
Bibliographic record
Abstract
Impact assessment (IA) involves complex interactions among societal actors with diverse knowledge systems and worldviews (ontological pluralism) that ideally combine to both define and support societal goals, such as sustainable development. An often acknowledged but rarely explored concept in these efforts is research capacity — the ability of a group to engage, produce, maintain and use knowledge — and associated implications for pluralistic process outcomes. This paper presents an embedded case study of the IA policy network in the Yukon Territory, Canada, to explore the various roles of research capacity in a well-established IA process where Indigenous and public representation are guaranteed, as is financial support for boundary spanning and knowledge brokering roles to support pluralism. Using Rapid Policy Network Mapping, we examine the formal and informal connections amongst IA policy actors and identify sources and flows of knowledge throughout the network. Results indicate that while research capacity is critical to well-functioning IA processes in the Yukon Territory, the ability of the IA policy network to source, disseminate and engage new knowledge is limited. Important boundary spanning ‘choke points’ can act as both facilitators and barriers, based on the capacity of the knowledge brokers occupying these spaces. The findings inform policy efforts to ensure inclusion and advance pluralism in IA processes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".