Trudeau punta alle prossime elezioni e opera un “rimpastone” per dare nuovo slancio all’azione di Governo
Bibliographic record
Abstract
In un quadrimestre (maggio-agosto 2023) tristemente segnato dal divampare di terribili incendi boschivi, che hanno devastato, da costa a costa, una superficie record di oltre centocinquantamila chilometri quadrati, pari a circa il 4% delle aree forestali del Canada, a surriscaldarsi è stato anche il clima politico. Il Primo ministro liberale Justin Trudeau, in poche mosse, ha infatti prepotentemente proiettato se stesso, il suo partito e il suo minority Government verso le prossime elezioni, le quali – salva l’ipotesi, tutt’altro che improbabile, di una richiesta di scioglimento anticipato della Camera dei Comuni – si terranno tra poco più di due anni, il 20 ottobre del 2025.
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.005 |
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; both teacher heads agree on what is shown here.
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".