PRIVACY_AND_DISCLOSURE.md

Privacy and Disclosure Report

1. Scope

This note documents the public-release privacy posture of spain-reference-personas-2025-v0.1. It is a release-level disclosure report for a synthetic benchmark substrate, not a formal certified re-identification study against protected source microdata.

2. What is not published

The release does not expose the following as stable public fields:

• exact date of birth
• street address or exact municipality-level residence
• email address
• phone number
• document number
• stable public full-name column
• real employer name
• real school name
• direct contact identifiers of any kind

3. Structural safeguards in the public package

3.1 Synthetic identity and linkage

• Persons are keyed by synthetic_person_id.
• Households are keyed by household_id.
• Identifiers are synthetic release artifacts only.

3.2 Geographic abstraction

• Public geography is represented at region and municipality-class level.
• Exact local addresses are not published.
• Household context is represented through categorical abstractions rather than fine-grained real-world household records.

3.3 Household abstraction

• Household composition is encoded through counts and grouped household types.
• Economic context is binned through tenure, burden, vehicle access, and consumption-constraint categories.
• Narrative views do not reveal exact household addresses or named co-residents.

3.4 Narrative safeguards

• Public Spanish views are derived from structured fields.
• Views are designed for prompt usefulness, not for real-person imitation.
• Release tests explicitly block internal enum leakage in the public narrative layer.
• Public views do not include contact details or precise personally identifying narratives.

4. Release audit summary

Measured from v0.1:

• Personas: 1,000,000
• Low disclosure-risk rows: 829,478 (82.948%)
• Moderate disclosure-risk rows: 166,341 (16.634%)
• High disclosure-risk rows: 4,181 (0.418%)
• Low uncertainty rows: 662,826 (66.283%)
• Medium uncertainty rows: 200,489 (20.049%)
• High uncertainty rows: 136,685 (13.668%)

Interpretation:

• The released package is overwhelmingly tagged low or moderate on internal disclosure heuristics.
• A small high-risk tail remains visible in metadata so downstream users can review or exclude it in stricter workflows.

5. Residual risk and caveats

This release should still be treated cautiously.

• Synthetic data can preserve sensitive structural patterns even when it excludes direct identifiers.
• Narrative views may feel realistic enough to encourage over-interpretation of individual records.
• Disclosure-risk tags are heuristic metadata, not a legal certification of zero re-identification risk.

6. Recommended handling for downstream users

• Use aggregate or subgroup analysis rather than point claims about any single synthetic person.
• Exclude high disclosure-risk rows when running especially conservative public demos.
• Use population_weight for macro summaries and publish methodology notes with any released findings.
• Avoid marketing, persuasion, or targeting claims framed as if the dataset were real survey microdata.

7. Relationship to evaluation and governance

This report should be read together with:

• DATASHEET.md
• EVALUATION_REPORT.md
• EVALUATION_METRICS.json

8. Bottom line

v0.1 is suitable for research, simulation, and benchmark development as a synthetic reference package. It should not be treated as a substitute for regulated disclosure review in high-stakes production settings.