---
license: mit
language:
- en
tags:
- construction-safety
- osha
- regulatory-compliance
- low-resource
- niche-domain
size_categories:
- 10K<n<100K
---

# Construction Code-Citation Corpus v1

Open dataset of construction-site incident narratives paired with OIICS
hazard codes (event, source, nature, body) and OSHA 29 CFR 1926 citation
candidates. Built for the [Adaption Labs AutoScientist Challenge](https://adaptionlabs.ai/auto-scientist)
("All Other Domains" category).

## Sources

- **OSHA Severe Injury Reports** (DOL, public domain): 2015-01 → 2025-08,
  103,750 records. Each row has `Final Narrative` (incident text) plus
  OIICS classification codes for the event, source, nature, and body part.
- **OSHA 29 CFR 1926** (eCFR snapshot 2025-09-16, public domain): 304
  sections with explicit citations and full regulatory text.

## Schema

Each row in the canonical jsonl:

```json
{
  "id": "<SIR ID>",
  "input": "<Final Narrative>",
  "hazards": [{
    "code_event":  {"id": "<OIICS event>",  "title": "..."},
    "code_source": {"id": "<OIICS source>", "title": "..."},
    "code_nature": {"id": "<OIICS nature>", "title": "..."},
    "code_body":   {"id": "<OIICS body>",   "title": "..."},
    "severity": "low|moderate|high"
  }],
  "citations": [],
  "naics": "<6-digit NAICS>",
  "naics_subsector": "<4-digit>",
  "event_date": "YYYY-MM-DD",
  "inspection_nr": "<int or null>",
  "source": "sir",
  "split": "train|dev|test"
}
```

The `citations` field is empty in v1 (SIR does not carry OSHA standard
citations directly). Citation supervision comes from a separate join on
`inspection_nr` to the DOL OSHA enforcement violations corpus, planned for v2.

## Splits

Stratified by NAICS subsector (first 4 digits), 70/15/15.

- train: 72,467
- dev:   15,410
- test:  15,873  (SHA-256 `c9490ed3...`, hash-pinned, never re-shuffled)

## Known biases

- SIR over-represents severe injuries (hospitalization, amputation, loss of
  eye) — the corpus is by definition skewed toward high-severity events.
- Source-code distribution has a heavy long tail: 1,478 unique codes, top-75
  cover only 57% of records. Models will need either a code-collapse strategy
  or hierarchical (division-level) prediction.

## License

MIT (this dataset). OSHA SIR is public domain. OSHA 29 CFR 1926 text is
public domain.

## Citation

If you use this dataset, please cite:

```
@misc{construction-code-corpus-2026,
  title  = {Construction Code-Citation Corpus v1},
  author = {Oversite Innovations},
  year   = {2026},
  note   = {Built for the Adaption Labs AutoScientist Challenge}
}
```