La pandemia che ha sconvolto il mondo: dati e tendenze internazionali nella percezione pubblica
Bibliographic record
Abstract
L’Annuario Scienza Tecnologia e Società, realizzato da Observa Science in Society, propone, in forma sintetica e accessibile, una raccolta aggiornata dei dati e delle informazioni provenienti dalle più accreditate fonti nazionali e internazionali, utili per comprendere lo stato e le trasformazioni della ricerca e dell’innovazione nella nostra società. Giunto alla diciassettesima edizione, il volume si caratterizza quest’anno per l’attenzione dedicata al tema delle tecnologie digitali e delle percezioni della pandemia da Covid-19. \nIl secondo capitolo, di Valeria Occelli e Barbara Saracino, è dedicato al confronto dei dati raccolti dall’Osservatorio sulle percezioni della pandemia nei primi mesi dell’emergenza con quelli di ricerche svolte con lo stesso metodo in Argentina, Canada, Corea del Sud, Finlandia, Germania, Malesia, Portogallo, Regno Unito, Romania, Spagna, Sudafrica, Svezia e Stati Uniti.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".