Fast Synthesis: qualitative analysis of gender

For qualitative researchers: prioritize transparent codebooks that capture nodes for funding, training access, decision-making, cooperative support, and social norms.

Triangulate, map themes back to specific participant groups (women vs men vs youth) and sites (An Thanh 3 vs Long Duc).

Report frequencies and co-occurrence, show how often “training access” co-occurs with “women” and “cooperative support” to make the case for targeted interventions.

For UX and program designers: design interventions with gendered interaction points, because when and where training happens matters (time, childcare, male-dominated meeting norms).

Use sentiment and needs-derived quotes to test messaging that increases women’s enrollment in technical training.

A/B test delivery channels (cooperatives vs. government extension) and track uptake by gender.

For policy and evaluation teams: translate qualitative themes into KPIs (for example, percentage of technical trainings with at least 30% women attendance; percentage of households reporting joint decision-making).

Fund multi-year pilots, not one-off trainings, the paper shows short project cycles erode gains.

Build local monitoring to capture gendered impacts of low-emission practices (land tenure, income, time use).

This subsection demonstrates how Evidano handles mixed inputs: import transcripts, policy PDFs, survey spreadsheets, and FGDs in minutes, useful for papers like the PLOS study that combine document types.

Use automated transcription with custom dictionaries (local names and terms) and PII redaction to prepare interview and FGD audio quickly.

This subsection explains coding and quantification in Evidano: auto-suggest codes from your corpus and generate a reproducible codebook, then run thematic, frequency, and co-occurrence analyses to see which barriers cluster with gendered groups.

Compare segments (women vs men vs youth, commune A vs B) using cross-segment analysis to reproduce findings such as 83% of households reporting men as primary training recipients.

This subsection shows reporting outputs: export stakeholder-ready visuals such as word clouds, thematic hierarchies, co-occurrence networks, and quote-by-theme exports that map to policy recommendations.

Use AI chat over your documents to ask targeted queries (for example, “show quotes where women describe barriers to subsidy application”) and produce draft memos.

This subsection addresses data security: data is encrypted and never used to train third-party models, essential when working with sensitive human-subjects data like the Soc Trang interviews.

Facilitate ethical sharing, control access for collaborators and prepare data packages for reviewers while respecting privacy agreements.

The PLOS Soc Trang study found insufficient funding, limited training access for women, and top-down implementation as the main barriers that limit gender-responsive low-emission transitions. The paper triangulated these barriers across policy documents, 24 KIIs, 24 household surveys, and 6 FGDs. Read the original study at PLOS Sustainability & Transformation.

The study used mixed methods: policy review, 24 key informant interviews (12 men, 12 women), 24 household surveys, and 6 FGDs, with fieldwork conducted May–Oct 2024. The sample included provincial officers, the Women’s Union, the Farmers Union, and random household samples across two communes.

Researchers can reproduce the analysis by gathering all materials, transcribing and normalizing terms, auto-coding, curating a codebook, validating coding on a sample, running frequency and co-occurrence analyses, and performing cross-segment comparisons. Follow the seven-step checklist in this post for a reproducible workflow.

Evidano supports ingestion and cleaning of mixed inputs, automated transcription with custom dictionaries and PII redaction, auto-suggested codes and reproducible codebooks, cross-segment analyses, exportable visuals, AI-assisted query drafting, and secure data controls. See the platform overview in the “Do more, faster with Evidano” section.