What Works for Whom in Public Employment Policy?
Notice bibliographique
Résumé
What works for whom in public employment policy? 1 participation were reported.Estimates of impacts on EI receipt were rarely statistically significant. Employment Assistance Services (EAS).These programs are generally short and relatively low-cost.Often EAS are combined in action plans with other interventions.Because of this complexity, evaluations of EAS have tended to focus on the group of "EAS-only" claimants.According to the British Columbia data, these represent perhaps 65 percent of individuals who received any EAS-related services, but a much smaller fraction of total EAS services provided (because those with an Employment Benefits intervention tend to have more EAS interventions than do members of the EAS-only group).The extent to which the EAS-only group is representative of all EAS participants has not been explicitly addressed in the evaluations, but on a priori grounds it seems plausible that this group might have more successful employment experiences than the other EAS participants.Results for active claimants were generally not statistically significant for employment and earnings, with the exception of one jurisdiction where an earnings increase was estimated.In part, this may have resulted from the difficulty of detecting such impacts given the small sample sizes available in the evaluations.For EI weeks, five out of eight evaluations generated statistically significant impacts; these included both positive and negative results.Given the mixed results, no overall conclusions can be drawn about the impact of EAS-only in the EBSM context.EAS participants did report strong levels of program satisfaction, job readiness, and interest in further training. Lessons Learned and Knowledge GapsWe list the lessons learned and the remaining gaps in knowledge about effects of EBSM operated under LMDA in the provinces and territories.Likely gaps concern effects by participant characteristics, program features, labour market conditions, and bundling or sequencing of services. Skills Development.Sample size restrictions generally prevented the evaluations from estimating effects of SD separately for subgroups of participants.A few of the evaluations did report that women had somewhat more favorable overall impacts on employment and earnings than men, though these results were generally not reported separately for SD participants only.In the evaluations that were able to estimate gender-specific impacts for SD participants only, gains for men often exceeded those for women.Hence, the EBSM results may not precisely mirror the international finding that women are more likely to benefit from training than men.Estimated impacts of SD on former claimants were more variable than were SD impact estimates for active claimants.This larger variance in results may in part be explained by the difficulties that some of the evaluations had in identifying a proper comparison group for former claimants, some of whom had been out of the labour force for some time.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,017 | 0,050 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,005 | 0,006 |
| Communication savante | 0,015 | 0,015 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,006 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,036 | 0,006 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».