Community Response and Engagement During Extreme Water Events in Saskatchewan, Canada and Queensland, Australia
Bibliographic record
Abstract
Technology alone cannot address the challenges of how societies, communities, and individuals understand water accessibility, water management, and water consumption, particularly under extreme conditions like floods and droughts. At the community level, people are increasingly aware challenges related to responses to and impacts of extreme water events. This research begins with an assessment of social and political capacities of communities in two Commonwealth jurisdictions, Queensland, Australia and Saskatchewan, Canada, in response to major flooding events. The research further reviews how such capacities impact community engagement to address and mitigate risks associated with extreme water events and provides evidence of key gaps in skills, understanding, and agency for addressing impacts at the community level. Secondary data were collected using template analysis to elucidate challenges associated with education (formal and informal), social and political capacity, community ability to respond appropriately, and formal government responses to extreme water events in these two jurisdictions. The results indicate that enhanced community engagement alongside elements of an empowerment model can provide avenues for identifying and addressing community vulnerability to negative impacts of flood and drought.
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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.003 |
| 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".