Reaching substantive female representation among decision-makers: A qualitative research study of gender-related experiences from the health sector in Mozambique
Notice bibliographique
Résumé
BACKGROUND: Achieving significant female representation in government at decision-making levels has been identified as a key step towards achieving gender equality. In 2015, women held 39.6% of parliamentary seats in Mozambique, which is above the benchmark of 30% that has been suggested as the turning point for minority representation to move from token status to having a sizable impact. We undertook a study to identify gender-related barriers and facilitators to improving women-centered policies in the health sector. METHODS: We conducted in-depth interviews with 39 individuals (32 women, 7 men) involved at a senior level in policy making or implementation of woman-centric policies within the Mozambique Ministry of Health and affiliated institutions. We used a semi-structured interview guide that included questions on difficulties and facilitating factors encountered in the policy making process, and the perceived role of gender in this process. We used both deductive and inductive analysis approaches, starting with a set of pre-identified themes and expanding this to include themes that emerged during coding. RESULTS: Our data suggest two main findings: (1) the women who participated in our study generally do not report feeling discrimination in the workplace and (2) senior health sector perceive women to be more personally attuned to women-centric issues than men. Within our specific sample, we found little to suggest that gender discrimination is a problem professionally for female decision-makers in Mozambique. However, these findings should be contextualized using an intersectional lens with recognition of the important difference between descriptive versus substantive female representation, and whether "percentage of women" is truly the best metric for gaging commitment to gender equality at the policy making level. CONCLUSIONS: Mozambique's longstanding significant representation of women may have led to creating an environment that leads to positive experiences for female decision-makers in the government. However, while the current level of female representation should be celebrated, it does not negate the need for continued focus on female representation in decision-making positions.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».