Qualitative analysis of gender in low-emission food systems

This post shows how to convert the PLOS Soc Trang case study into actionable, reproducible recommendations using rapid qualitative synthesis and AI-assisted tools.

• Pham et al. (Received July 14, 2025; Accepted May 27, 2026; Published July 1, 2026) collected data May-Oct 2024: 24 key informant interviews, 6 FGDs, and 24 household surveys in two communes (An Thanh 3 and Long Duc).
• The main barriers reported are limited funding, weak coordination, and entrenched social norms that prevent gender-responsive low-emission policies from delivering at the local level.
• Researchers and program teams can move from descriptive findings to prioritized, fundable actions by using systematic qualitative synthesis (theme frequencies, co-occurrence, cross-segment comparisons) and AI-enabled workflows like Evidano.
• The post provides a practical seven-step checklist that can reproduce Soc Trang–style insights in about two weeks using centralized inputs, AI-assisted coding, and stakeholder validation.

Pham et al.'s PLOS paper matters because it empirically shows a policy-to-practice gap in Soc Trang Province, Vietnam, for gender-responsive low-emission food system policies.

Pham et al. (Received July 14, 2025; Accepted May 27, 2026; Published July 1, 2026) use Soc Trang Province as a multiple-case empirical study to examine why gender-responsive low-emission food system policies are not delivering at the local level; full paper: PLOS Sustainability & Transformation.

• Key problem: policy design exists, but implementation falters due to limited funding, weak coordination, and entrenched social norms.
• What researchers need: systematic qualitative synthesis (themes, sentiment, co-occurrence) and robust cross-segment comparisons (women vs men vs youth, commune A vs B).
• Payoff: use AI-enabled qualitative research to move from descriptive findings to prioritized, fundable actions.

The study combined a policy review with mixed qualitative methods: 24 key informant interviews, 6 FGDs, and 24 household surveys, producing thematic analysis and descriptive statistics.

Transcripts were open-coded and analyzed in NVivo; thematic analysis and simple descriptive statistics (frequencies, percentages) were triangulated to validate findings.

• Scope: Soc Trang Province (An Thanh 3 and Long Duc communes), agriculture, aquaculture, forestry, livestock.
• Core outputs: themes on funding instability, information access, gendered training gaps, and top-down implementation constraints.
• Limitations noted: small sample sizes for generalization, restricted data sharing due to ethics.

This checklist gives seven practical steps to convert Soc Trang–style field data into prioritized recommendations in about two weeks.

• 1) Centralize inputs: upload transcripts, survey CSVs, and policy PDFs into Evidano (day 1).
• 2) Transcribe and translate (if needed) with custom dictionary; apply PII redaction (days 1–2).
• 3) Import or draft an initial codebook (policy, funding, training, norms, participation) and run AI-assisted coding (days 2–4).
• 4) Produce thematic frequency tables, co-occurrence networks, and hierarchical code maps; filter by segment (women/men/youth; commune) (days 4–6).
• 5) Validate with 3–5 domain experts: correct codes, tag key quotes (days 6–8).
• 6) Create a short policy brief with top 3 prioritized interventions and evidence snippets (days 8–10).
• 7) Share an interactive report (visuals and searchable quotes) with stakeholders for rapid feedback and next-step funding proposals (days 10–14).

Pham et al.'s July 1, 2026 study makes the gap between gender-aware policy and local practice visible and actionable.

If your team needs to move from narrative findings to prioritized interventions quickly, apply the seven-step checklist above and instrument your analysis with Evidano to produce reproducible, segment-sensitive evidence.

• Start a pilot: upload a single FGD transcript and one survey into Evidano and run thematic and cross-segment analyses to see immediate value.
• For a demo and to test this workflow on your data, visit Evidano and to start now, Try Evidano for free.