PROTOCOL: Vocational and business training to increase women's participation in higher skilled occupations in low‐ and middle‐income countries: protocol for a systematic review
Notice bibliographique
Résumé
Th e Pr o b le mAlthough women's employment possibilities have improved with the rise of globalization, wom en in low-and m iddle-income countries tend to be overrepresented in informal labour markets, work in precarious conditions, receive lower salaries than m en, and have few opportunities for learning and advancem ent (Borges Månsson & Färnsveden, 20 12).Duflo (20 12) reports that "women are less likely to work, they earn less than men for similar work, and are m ore likely to be in poverty even when they work" (p.1052).Women often perform jobs that have low skill requirements and frequently work in occupations that are highly feminized, tend to be less socially valued, and pay lower wages (Aedo & Walker, 20 12; Altm an, 20 0 6; International Labour Organization [ILO], 20 15; ILO, 20 16).A recent ILO report has documented the limited opportunities for women in the labour market (ILO, 20 16).The report shows that women face higher unemployment and underem ploym ent than m en, are m ore often em ployed in the inform al labour m arket and in family enterprises, and are overrepresented in lower skill sectors.For exam ple, a greater proportion of women are employed in the services sector (61.5 per cent versus 42.6 per cent of m en), where wom en are particularly overrepresented in fem inized positions such as "clerical, services, and sales" and "elementary" occupations (ILO, 20 16).Moreover, although m en and wom en face equal rates of wage and salaried em ploym ent (around 52 per cent), m en are m ore likely to own their own business than wom en (3.7 per cent of men versus 1.4 per cent of wom en).Meanwhile, and while data on inform al sector employm ent is scant, wom en are 'believed to constitute most of the informal workforce in the developing world' (UNGEI 20 12).Work in the informal sector is characterised by low pay and low productivity (ILO, 20 16).Wom en working in inform al em ploym ent do not gain access to social protection, such as pensions, and this m ay contribute to the fact that 71.8 per cent of all em ployed wom en do not have any type of m aternity protection (ILO, 20 16).A range of factors contribute to the high proportion of unemployed and underem ployed wom en.These factors include cultural norms regarding the place of wom en in em ploym ent, the role of wom en in domestic and care work, and the lack of adequate job m arket opportunities.Women all over the world spend a disproportionate am ount of tim e doing domestic and care work.This tim e com m itm ent is even higher in low-and middle-incom e countries, where the division of domestic labor often follows traditional patterns and wom en assume most, if not all fam ily responsibilities (ILO, 20 0 9).Wom en m ay also have a preference for jobs that are compatible with their domestic responsibilities, such as parttim e and flexible jobs, both of which are scarce in low-and middle-incom e countries (ILO, 20 0 9).H owever, even when part-tim e and flexible job opportunities exist, allowing wom en to combine work and family responsibilities, there is evidence that these jobs do not constitute 'a path to decent work' (ILO, 20 0 5).This lack of opportunities contributes to the choice of wom en to remain self-em ployed in sm all-scale enterprises or in dom estic and care 18911803, 2016, 1, Downloaded from https://onlinelibrary.
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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 | 0,028 | 0,060 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,005 |
| Méta-épidémiologie (sens large) | 0,021 | 0,014 |
| Bibliométrie | 0,009 | 0,008 |
| Études des sciences et des technologies | 0,004 | 0,004 |
| Communication savante | 0,009 | 0,010 |
| Science ouverte | 0,004 | 0,005 |
| Intégrité de la recherche | 0,007 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,205 | 0,023 |
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 ».