Direction, evidence grade, and study type are AI-generated labels (gpt-5-mini), not human-verified. Syntheses are LLM-written. "Tensions" are machine-detected candidates, not confirmed contradictions. A research-acceleration tool, not peer review.
How this is built →
1Distinct papers
6Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5128773603
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Flor Paz (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Inequality: 1 paper
Claim outcomes
- Social Protection: 1 paper
- Other: 1 paper
- Inequality: 1 paper
Papers in the OpenAlex view
Latest stored OpenAlex author observations only. Citation counts below are from the same provider and are not combined with other services.
Scroll the table horizontally to see every column.
| Paper | Author evidence | Date | Provider citations |
|---|---|---|---|
| Gender fundamentally alters who benefits from social protection in low- and middle-income countries, so policy tools — including AI systems used for targeting, monitoring and evaluation — must be designed with gender-disaggregated data, causal methods for subgroup effects, and governance safeguards to prevent reinforcing existing inequalities.openalex | Flor Paz provider id |
2026-03-10 | 0 |
Citation observation summary
OpenAlex supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 0 cumulative citations. This is a coverage summary, not an author score or h-index.