Advancing the scholarship and practice of stakeholder engagement in working landscapes: a co-produced research agenda
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Participatory approaches to science and decision making, including stakeholder engagement, are increasingly common for managing complex socio-ecological challenges in working landscapes. However, critical questions about stakeholder engagement in this space remain. These include normative, political, and ethical questions concerning who participates, who benefits and loses, what good can be accomplished, and for what, whom, and by who. First, opportunities for addressing justice, equity, diversity, and inclusion interests through engagement, while implied in key conceptual frameworks, remain underexplored in scholarly work and collaborative practice alike. A second line of inquiry relates to research-practice gaps. While both the practice of doing engagement work and scholarly research on the efficacy of engagement is on the rise, there is little concerted interplay among 'on-the-ground' practitioners and scholarly researchers. This means scientific research often misses or ignores insight grounded in practical and experiential knowledge, while practitioners are disconnected from potentially useful scientific research on stakeholder engagement. A third set of questions concerns gaps in empirical understanding of the efficacy of engagement processes and includes inquiry into how different engagement contexts and process features affect a range of behavioral, cognitive, and decision-making outcomes. Because of these gaps, a cohesive and actionable research agenda for stakeholder engagement research and practice in working landscapes remains elusive. In this review article, we present a co-produced research agenda for stakeholder engagement in working landscapes. The co-production process involved professionally facilitated and iterative dialogue among a diverse and international group of over 160 scholars and practitioners through a yearlong virtual workshop series. The resulting research agenda is organized under six cross-cutting themes: (1) Justice, Equity, Diversity, and Inclusion; (2) Ethics; (3) Research and Practice; (4) Context; (5) Process; and (6) Outcomes and Measurement. This research agenda identifies critical research needs and opportunities relevant for researchers, practitioners, and policymakers alike. We argue that addressing these research opportunities is necessary to advance knowledge and practice of stakeholder engagement and to support more just and effective engagement processes in working landscapes. Supplementary Information: The online version contains supplementary material available at 10.1007/s42532-022-00132-8.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.134 | 0.172 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.000 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it