Urban Forest Governance in the Face of Pulse Disturbances—Canadian Experiences
Bibliographic record
Abstract
"The sustainable provision of urban forest benefits can be threatened by the occurrence of sudden, major disturbance events, such as forest fires, insect outbreaks, and extreme weather events, which are considered to be “pulse” disturbance events from a socio-ecological systems perspective. Sound urban forestry programs are needed to prepare for these disturbances and reduce their negative impacts. To investigate the role of governance in building more resilient urban forest socio-ecological systems, the relation between pulse disturbances and urban forest governance was studied in 4 Canadian cities. Our study of local urban forestry included expert interviews with local urban forest governance actors, document analysis, and site visits. The Policy Arrangement Approach was applied to structure and analyse urban forest governance. Findings show that all cities had seen a development of their urban forestry programs and governance over time, such as development of staff and formal plans, as well as alliances with key partners. Pulse disturbances seem to have played an important role in the development and sometimes reorientation of urban forestry programs. Although disturbances often had devastating impacts, having a strong urban forestry program in place, including strong alliances with, e.g., industry partners or NGOs, was considered important for handling the aftermath of these events. Efforts had also been made to be better prepared for future disturbances through further professionalization, development of plans, guidelines, and best practices, capacity building through partnerships, and setting up better real-life information systems in support of decision making. Results can inform urban forest governance and urban forestry programs in Canadian cities and elsewhere."
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".