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README.md

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+---
+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}
+}
+```