Un espace de résilience dédié à la dépendance à l’électricité des infrastructures critiques municipales
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
This article addresses the growing vulnerability of municipal critical infrastructures to their dependence on electricity, a situation exacerbated by complex interdependencies. Major power outages, considered systemic risks, are difficult to anticipate and control. Moreover, within a given territory, such outages affect a wide range of infrastructures simultaneously. Consequently, consequence management requires collaborative and adaptive governance among all relevant stakeholders to mitigate impacts on populations. In this context, the concept of a resilience space is introduced. It is defined as a structured framework bringing together municipal actors and the power grid operator to strengthen both individual and collective resilience through enhanced cooperation. The central tool is the Common Situational Picture, which maps infrastructures’ response capacities and vulnerabilities, thereby supporting shared understanding and the development of adapted strategies. The implementation of the resilience space in the Montréal region has demonstrated significant benefits: improved identification of vulnerable sectors, adaptation of municipal emergency plans, and strengthened relationships among all involved stakeholders. The sustainability of this approach relies on clear governance, secure information sharing, and neutral leadership. It is becoming increasingly critical in the face of emerging challenges related to the energy transition and climate change.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 it