Co-production Through Volunteerism in Emergency Management: Drawing Lessons from Canada’s Syrian Refugee Resettlement Initiative
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
The field of emergency management has been increasingly encouraging the notion of emergency management as a shared, co-productive responsibility, with all members of the society having a role to play. In such whole-of-society efforts, volunteers play a direct role in the co-production of response outcomes. Canada’s mass resettlement of Syrian refugees in 2015 is a case in point, as Canadians rallied en masse to ensure the successful resettlement of thousands of Syrian refugees. In exploring the role of volunteers in this co-productive initiative, there are two important lessons for those in emergency management: The first involves learning from the volunteer management strategies implemented by resettlement agencies, which are applicable for any responding entity tasked with managing whole-of-society response efforts. The second (and perhaps more important) lesson is that those managing whole-of-society response efforts must recognize that value is co-created through three key relationships, a triad between volunteers, response entities, and those directly impacted by a disaster. Each of these relationships must be better understood and managed in order to achieve more effective emergency response outcomes in whole-of-society initiatives.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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