Peut-on favoriser l’inclusion sociale des jeunes par l’utilisation des médias sociaux?
Bibliographic record
Abstract
Les jeunes présentant une déficience intellectuelle (DI) vivent souvent de l’exclusion sociale. Ils semblent avoir un réseau d’amis très restreint, surtout à la fin de leur scolarisation. Or, l’utilisation des technologies de l’information et de la communication (TIC), et notamment celle des médias sociaux, favorise la participation sociale et le développement de liens familiaux ou amicaux. Les jeunes qui présentent une DI profitent-ils de cette technologie? Les TIC permettent-elles à ces jeunes de bénéficier d’un meilleur réseau de soutien personnel et social? Cette recension des écrits tente de répondre à cette question, et révèle que : 1) les TIC ne sont pas accessibles pour tous; et 2) l’utilisation des médias sociaux augmente les risques d’abus et de cybervictimisation.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".