Bibliographic record
Abstract
La ville intelligente est considérée par les territoires urbains comme la solution par excellence pour répondre aux enjeux démographiques, économiques, sociaux et environnementaux auxquels ils sont actuellement confrontés. Pourtant, entre l’optimisation technologique des infrastructures d’ingénierie urbaine, le développement d’une économie de start-up ou les sirènes de la gouvernance urbaine basée sur les données, il est bien difficile d’évaluer les effets sociaux de ces transformations numériques à moyen et long terme. Même si l’engagement des citoyens, la gouvernance ouverte ou le développement durable sont généralement associés au discours sur les villes intelligentes, les risques éthiques tels que le suivi individuel, le profilage socio-spatial, la justice spatiale ou l’inclusivité demeurent des enjeux importants. Cet article propose le modèle d’Inukshuk City, comme levier de développement d’une nouvelle forme d’intelligence urbaine.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".