拉丁美洲经济委员会-努力将性别观点纳入拉丁美洲和加勒比统计生产的主流（英）-2025_125页_3mb

报告摘要

Summary of Document: "Towards mainstreaming the gender perspective in statistical production in Latin America and the Caribbean"

This document provides a comprehensive guide to integrating a gender perspective into official statistics in Latin America and the Caribbean. It emphasizes gender mainstreaming, intersectionality, and autonomy frameworks to address gender inequalities through policy and statistical reforms.

Key Points:

Latin America and the Caribbean (LAC) countries are advancing gender equality through the Regional Gender Agenda, supported by frameworks like the Montevideo Strategy and the SDGs (especially SDG 5). Data is essential for monitoring progress and designing effective policies.
Gender Concepts:
- Gender Mainstreaming: Integrating gender analysis into all stages of policy and statistical processes to ensure equality.
- Intersectionality: Examining how gender intersects with race, class, disability, etc., to address multiple forms of discrimination.
- Autonomy: Focusing on women's economic, physical, and decision-making autonomy.
- Sex Disaggregation: Mandatory inclusion of sex as a basic classification in statistics.
Policy Frameworks: International instruments like the Beijing Declaration, CEDAW, and UN SDGs set standards. Regionally, agreements on gender violence, unpaid work, and gender statistics guide implementation.
Statistical Process Approaches:
- Phases covered: Needs Specification, Design, Build, Collect, Process, Analyze, Disseminate, Evaluate.
- Key actions:
  - Use inclusive language.
  - Train staff on gender issues.
  - Involve users and stakeholders throughout the process.
  - Disaggregate data by sex and other intersecting variables.
  - Standardize methodologies and collaborate across institutions.
Regional Challenges and Good Practices:
- Funding: Volatility in international aid requires sustainable national investment.
- Standardization: Harmonizing methods for issues like time-use, gender violence, etc.
- Innovations: Using big data, geospatial analysis, and participatory methods.
- Good Practices: Strong institutional partnerships (e.g., NSOs + WGMs) and sex-disaggregated surveys.
Contribution of this Document: Builds on guidelines from the Statistical Conference of the Americas and Regional Conference on Women, serving as a tool for enhancing gender-responsive data production.