# Datasheet: Spain Reference Personas Frontier

## 1. Overview

Spain Reference Personas Frontier is a synthetic reference population and benchmark package for Spanish-language LLM work grounded in the territorial, household, cultural, linguistic, and civic structure of Spain. The dataset is built for controllable evaluation and simulation, not for long-form biography generation as an end in itself.

| Snapshot fact | Value |
| --- | ---: |
| Release id | spain-reference-personas-2025-v0.1 |
| Population reference date | 2025-12-31 |
| Release date | 2026-03-20 |
| Adult personas | 1,000,000 |
| Households | 536,741 |
| Persona views | 6,350,524 |
| Actor-state rows | 1,000,000 |
| Benchmark tasks | 1,800 |

## 2. Motivation

The central design decision is that a persona should be a package. Serious LLM workflows need structured controls for filtering, compact prompt views for conditioning, mutable state for event-driven simulation, and benchmark tasks for evaluation. The release therefore prioritizes usefulness, composability, and reproducibility over narrative volume.

The project takes inspiration from multi-view persona releases such as [Nemotron Personas USA](https://huggingface.co/datasets/nvidia/Nemotron-Personas-USA), but adapts that idea to Spain-specific benchmarking, household-aware simulation, and explicit held-out evaluation splits.

## 3. Population universe

- Universe: adult residents of Spain, age 18+.
- Scope: Spain-specific, not a generic Spanish-language population.
- Minors are represented only through household context in v0.1.
- Public views are Spanish-first.
- Co-official languages and immigrant-language repertoire are modeled as metadata.
- Public geography is limited to region and municipality class.

## 4. Artifact inventory

| Artifact | Rows | Grain | Role |
| --- | ---: | --- | --- |
| persona_core.parquet | 1,000,000 | person | Stable synthetic adult structure |
| household_core.parquet | 536,741 | household | Household composition and economic context |
| persona_views.parquet | 6,350,524 | person-view | Spanish LLM-facing renderings with token budgets |
| actor_state_init.parquet | 1,000,000 | person | Mutable simulation-state scaffold |
| benchmark_tasks.parquet | 1,800 | task | Tasks, splits, scoring targets, replay seeds |
| source_registry.parquet | 11 | source | Release-level source inventory |
| field_provenance.parquet | 13 | field-group | Per-field provenance mapping |
| EVALUATION_METRICS.json | 1 | release | Machine-readable evaluation summary |

## 5. Intended uses

| Workflow | Recommended artifacts | Why |
| --- | --- | --- |
| Polling and policy tradeoffs | persona_core, persona_views, benchmark_tasks | structured retrieval plus policy framing and replayable task scoring |
| Consumer and inflation studies | household_core, persona_core, consumer_view | household burden and purchase constraints materially affect prompts |
| Media and event-reaction simulation | actor_state_init, dialogue_view, culture_view | mutable recency and media exposure matter for scenario responses |
| Sociological subgroup design | persona_core, household_core | region, language, migration, household form, and values remain queryable |
| Multi-turn agent benchmarks | all configs | stable identity, compact views, mutable state, and tasks remain separate |

## 6. Non-goals and inappropriate uses

- Replacing field surveys or administrative microdata.
- Approximating or identifying real individuals.
- Simulating minors as public personas in v0.1.
- Treating synthetic narrative as literal biography truth.
- Making election or policy forecasts without external validation.

## 7. Construction pipeline

1. Household synthesis.
2. Adult assignment within households.
3. Geographic and life-stage allocation.
4. Education, labor, occupation, income, and socioeconomic assignment.
5. Migration and language-domain assignment.
6. Digital/media and cultural-profile assignment.
7. Civic, political, consumer, and latent-value assignment.
8. Weight calibration and disclosure tagging.
9. Persona-view rendering from structured fields.
10. Actor-state initialization.
11. Benchmark-task generation.

## 8. Schema overview

### 8.1 persona_core

- identity and linkage: synthetic_person_id, household_id, snapshot_id
- geography: region, municipality_class, urban_rural
- demography: age, age_group, gender, migration_background, years_in_spain_band
- education and work: education, labor_status, occupation_class, socioeconomic_tier, income
- language: first_language, language_of_identification, home_language, work_or_study_language, spanish_proficiency, immigrant_language_repertoire
- digital/media: device_access, internet_intensity, media_habit_cluster, primary_news_sources, platform_mix
- culture/leisure: reading_frequency, gaming_frequency, sports_affinity, cultural_interests, community_participation
- civic/political structure: turnout_propensity, institutional_trust, political_attention, ideology_interval_low, ideology_interval_high, issue_salience_top3
- consumer structure: decision_style, price_sensitivity, sustainability_orientation, local_purchase_preference, brand_loyalty
- governance: population_weight, benchmark_sampling_weight, uncertainty_level, disclosure_risk_level, field_provenance_ids

### 8.2 household_core

- composition: adult_count, minor_count, household_type, caregiving_role
- settlement: region, municipality_class, urban_rural
- economic context: tenure_band, housing_cost_burden, vehicle_access, consumption_constraint

### 8.3 persona_views

- micro_card
- standard_card
- policy_view
- consumer_view
- culture_view
- dialogue_view
- extended_profile for a stratified subset

### 8.4 actor_state_init

- current mood
- attention budget
- event sensitivity
- persuasion resistance
- memory style
- recent-media diet
- shopping context and preference volatility

### 8.5 benchmark_tasks

- task identity: id, family, split, synthetic_person_id
- binding: persona_view, scoring_target, allowed_context
- reproducibility: prompt_template_id, replay_seed
- task content: prompt

## 9. Provenance regime

| Provenance tier | Meaning |
| --- | --- |
| Official statistics | Macro population anchors and structural baselines |
| Institutional or survey inputs | Conditioning inputs for language, media, civic, and social structure |
| Modeled latent variables | Values, motivations, and abstract behavioral tendencies |
| Rendered narrative | Spanish textual views derived from structured inputs |

Companion provenance artifacts:

- source_registry.parquet for release-level source records
- field_provenance.parquet for field-group attribution

## 10. Quality controls

| Control | Result |
| --- | ---: |
| Region share MAE | 0.022 pp |
| Age share MAE | 2.95 pp |
| View budget compliance | 100% |
| Benchmark families | 9 |
| Benchmark split types | 4 |
| High disclosure-risk rows | 0.418% |

## 11. Representative population structure

| Signal | Result |
| --- | ---: |
| First language = Spanish | 76.896% |
| Migration background other than Spain-born | 22.516% |
| Households with minors | 38.013% |
| Private rent | 39.471% |
| High housing-cost burden | 29.676% |
| Tight consumption constraint | 22.080% |

## 12. Privacy and disclosure posture

Not published as stable public fields:

- exact birth dates
- street addresses
- email addresses
- phone numbers
- document numbers
- real employer names
- real school names
- stable public full-name columns

Narrative views are derived from structured fields and are designed for prompt usefulness rather than real-person imitation.

## 13. Current limitations

- The age profile remains the main demographic calibration gap.
- Household, media, and latent-value fields are synthetic abstractions and should be validated against the downstream task.
- The benchmark matrix is packaged, but live cross-model lift is not part of the release card.
- Disclosure flags help triage rows for review but are not a substitute for formal re-identification analysis.

## 14. Distribution and maintenance

- Data license: CC BY 4.0
- Release form: dated snapshot
- Default HF viewer config: persona_core
- Change policy: new versioned release rather than silent mutation of v0.1

## 15. Companion documents

- README.md
- EVALUATION_REPORT.md
- EVALUATION_METRICS.json
- PRIVACY_AND_DISCLOSURE.md

## 16. Citation

Cite the Hugging Face repository and the release id spain-reference-personas-2025-v0.1.