build(stage1): create primary outcome response layer
This commit is contained in:
Jinotech
@@ -430,7 +430,7 @@ Generated from the direct-source registry and audits by `build_primary_outcome_p
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- source conflicts or evidence gaps: {conflicts}
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- human reviewers recorded: 0
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The package does not satisfy Gate 1 by itself. Two actual human reviewers must independently sign every primary-outcome item; `responses_long.parquet` is not yet built; NSDUH youth attempt is absent from local public-use microdata; and several design and administered-language fields remain provisional.
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The package does not satisfy Gate 1 by itself. `responses_long.parquet` has passed structural validation, but two actual human reviewers must independently sign every primary-outcome item; NSDUH youth attempt is absent from local public-use microdata; and several design and administered-language fields remain provisional.
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"""
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(STAGE1 / "primary_outcome_package.md").write_text(text, encoding="utf-8")
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@@ -0,0 +1,241 @@
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"""Build the Gate-1 long response table from source-verified primary outcomes."""
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from __future__ import annotations
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import csv
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import hashlib
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import json
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from collections import Counter
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from pathlib import Path
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from typing import Any
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import duckdb
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import pyarrow as pa
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import pyarrow.parquet as pq
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ROOT = Path(__file__).resolve().parents[2]
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STAGE1 = ROOT / "research" / "stage1"
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GSHS = ROOT / "Dataset" / "GSHS-全球学生健康调查数据" / "GSHS" / "01_data" / "GSHS.csv"
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YRBS_DIR = ROOT / "Dataset" / "可直接分析数据包_NSDUH_YRBS" / "YRBS" / "full_by_year"
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NSDUH = ROOT / "Dataset" / "可直接分析数据包_NSDUH_YRBS" / "NSDUH" / "nsduh_2021_2024_full.parquet"
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OUTPUT = ROOT / "Dataset" / "可直接分析数据包_NSDUH_YRBS" / "harmonization" / "responses_long.parquet"
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MANIFEST = STAGE1 / "responses_long_manifest.json"
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REPORT = STAGE1 / "responses_long_audit.md"
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SCHEMA = pa.schema([
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("respondent_id", pa.string()),
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("survey_id", pa.string()),
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("component_id", pa.string()),
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("survey_year", pa.int16()),
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("item_version_id", pa.string()),
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("raw_response", pa.string()),
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("canonical_response", pa.string()),
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("eligibility", pa.string()),
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("observed_status", pa.string()),
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("missing_type", pa.string()),
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("source_row", pa.int64()),
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])
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def load_csv(path: Path) -> list[dict[str, str]]:
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with path.open(encoding="utf-8-sig", newline="") as handle:
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return list(csv.DictReader(handle))
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def normalized_code(value: Any) -> str:
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if value is None:
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return "<missing>"
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if isinstance(value, float) and value.is_integer():
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return str(int(value))
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text = str(value).strip()
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if not text:
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return "<missing>"
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if text.endswith(".0"):
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try:
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return str(int(float(text)))
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except ValueError:
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pass
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return text
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def sha256(path: Path) -> str:
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digest = hashlib.sha256()
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with path.open("rb") as handle:
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for block in iter(lambda: handle.read(1024 * 1024), b""):
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digest.update(block)
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return digest.hexdigest()
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class LongWriter:
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def __init__(self, path: Path, response_map: dict[tuple[str, str], dict[str, str]]) -> None:
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path.parent.mkdir(parents=True, exist_ok=True)
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self.writer = pq.ParquetWriter(path, SCHEMA, compression="zstd")
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self.response_map = response_map
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self.buffer: list[dict[str, Any]] = []
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self.rows_by_survey: Counter[str] = Counter()
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self.rows_by_item: Counter[str] = Counter()
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self.observed_status: Counter[str] = Counter()
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self.missing_types: Counter[str] = Counter()
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def add(self, *, respondent_id: str, survey_id: str, component_id: str, year: int,
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item_version_id: str, raw_value: Any, eligibility: str, source_row: int) -> None:
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raw_code = normalized_code(raw_value)
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key = (item_version_id, raw_code)
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if key not in self.response_map:
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raise ValueError(f"No response dictionary entry for {key}")
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mapping = self.response_map[key]
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observed = mapping["is_observed_response"] == "true"
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missing_type = mapping["missing_type"]
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status = "observed" if observed else (missing_type or "missing")
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survey = item_version_id.split("::", 1)[0]
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self.buffer.append({
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"respondent_id": respondent_id,
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"survey_id": survey_id,
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"component_id": component_id,
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"survey_year": year,
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"item_version_id": item_version_id,
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"raw_response": None if raw_code == "<missing>" else raw_code,
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"canonical_response": mapping["canonical_code"] or None,
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"eligibility": eligibility,
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"observed_status": status,
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"missing_type": missing_type or None,
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"source_row": source_row,
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})
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self.rows_by_survey[survey] += 1
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self.rows_by_item[item_version_id] += 1
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self.observed_status[status] += 1
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if missing_type:
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self.missing_types[missing_type] += 1
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if len(self.buffer) >= 50_000:
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self.flush()
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def flush(self) -> None:
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if self.buffer:
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self.writer.write_table(pa.Table.from_pylist(self.buffer, schema=SCHEMA))
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self.buffer.clear()
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def close(self) -> None:
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self.flush()
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self.writer.close()
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def main() -> None:
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item_rows = load_csv(STAGE1 / "item_bank.csv")
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dictionary_rows = load_csv(STAGE1 / "response_dictionary.csv")
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item_index = {(r["survey"], r["component_id"], r["source_variable"].lower()): r for r in item_rows}
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response_map = {(r["item_version_id"], r["raw_code"]): r for r in dictionary_rows}
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writer = LongWriter(OUTPUT, response_map)
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expected_rows: dict[str, int] = {}
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# GSHS: stream the large CSV, retaining only the seven source-verified components.
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gshs_components = {r["component_id"] for r in item_rows if r["survey"] == "GSHS"}
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gshs_vars = ["raw_mh_considersui", "raw_mh_plansui", "raw_mh_attemptsui"]
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with GSHS.open(encoding="utf-8-sig", newline="") as handle:
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reader = csv.DictReader(handle)
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for source_row, row in enumerate(reader, start=1):
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component = row["dataset_id"]
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if component not in gshs_components:
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continue
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year = int(str(row["survey_year"])[:4])
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survey_id = next(r["survey_id"] for r in item_rows if r["survey"] == "GSHS" and r["component_id"] == component)
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respondent = f"{component}::{row['id']}"
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for variable in gshs_vars:
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item = item_index[("GSHS", component, variable)]
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writer.add(respondent_id=respondent, survey_id=survey_id, component_id=component,
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year=year, item_version_id=item["item_version_id"], raw_value=row[variable],
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eligibility="eligible_administered_component", source_row=source_row)
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gshs_audit = json.loads((STAGE1 / "gshs_primary_outcome_component_audit.json").read_text(encoding="utf-8"))
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expected_rows["GSHS"] = sum(c["observed_rows"] for c in gshs_audit["components"] if c["primary_outcomes_observed"]) * 3
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# YRBS: all 17 annual full tables have passed source/layout and value-domain checks.
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yrbs_items = [r for r in item_rows if r["survey"] == "YRBS"]
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yrbs_respondents = 0
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for year in sorted({int(r["year"]) for r in yrbs_items}):
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annual_items = [r for r in yrbs_items if int(r["year"]) == year]
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columns = ["source_row", *[r["source_variable"].lower() for r in annual_items]]
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table = pq.read_table(YRBS_DIR / f"yrbs_{year}_full.parquet", columns=columns).to_pydict()
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yrbs_respondents += len(table["source_row"])
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for offset, source_row in enumerate(table["source_row"]):
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respondent = f"YRBS::{year}::{source_row}"
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for item in annual_items:
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variable = item["source_variable"].lower()
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writer.add(respondent_id=respondent, survey_id=item["survey_id"], component_id=item["component_id"],
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year=year, item_version_id=item["item_version_id"], raw_value=table[variable][offset],
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eligibility="eligible_sampled_student", source_row=int(source_row))
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expected_rows["YRBS"] = yrbs_respondents * 3
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# NSDUH: restrict to CATAG2=1 (12-17); attempt is documented but absent from public-use data.
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nsduh_items = [r for r in item_rows if r["survey"] == "NSDUH" and r["source_variable"] in {"YUSUITHK", "YUSUIPLN"}]
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nsduh_table = pq.read_table(NSDUH, columns=["YEAR", "QUESTID2", "CATAG2", "YUSUITHK", "YUSUIPLN"]).to_pydict()
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nsduh_youth = 0
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for offset, age_group in enumerate(nsduh_table["CATAG2"]):
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if normalized_code(age_group) != "1":
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continue
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nsduh_youth += 1
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year = int(nsduh_table["YEAR"][offset])
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annual_items = [r for r in nsduh_items if int(r["year"]) == year]
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respondent = f"NSDUH::{year}::{nsduh_table['QUESTID2'][offset]}"
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for item in annual_items:
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variable = item["source_variable"]
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writer.add(respondent_id=respondent, survey_id=item["survey_id"], component_id=item["component_id"],
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year=year, item_version_id=item["item_version_id"], raw_value=nsduh_table[variable][offset],
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eligibility="eligible_age_12_17", source_row=offset + 1)
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expected_rows["NSDUH"] = nsduh_youth * 2
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writer.close()
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con = duckdb.connect()
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path_sql = str(OUTPUT).replace("'", "''")
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totals = con.execute(f"SELECT count(*), count(DISTINCT respondent_id || '|' || item_version_id), count(DISTINCT item_version_id) FROM read_parquet('{path_sql}')").fetchone()
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null_checks = con.execute(f"SELECT count(*) FILTER (WHERE respondent_id IS NULL OR item_version_id IS NULL OR eligibility IS NULL OR observed_status IS NULL), count(*) FILTER (WHERE observed_status='observed' AND canonical_response IS NULL) FROM read_parquet('{path_sql}')").fetchone()
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bad_codes = con.execute(f"SELECT count(*) FROM read_parquet('{path_sql}') WHERE observed_status='observed' AND raw_response IS NULL").fetchone()[0]
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con.close()
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if totals[0] != totals[1]:
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raise AssertionError("respondent_id × item_version_id keys are not unique")
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if null_checks != (0, 0) or bad_codes:
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raise AssertionError(f"Long-table required-field/canonical checks failed: {null_checks=} {bad_codes=}")
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if totals[2] != 80:
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raise AssertionError(f"Expected responses for 80 locally analyzable items, found {totals[2]}")
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if dict(writer.rows_by_survey) != expected_rows:
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raise AssertionError(f"Source-derived row totals do not match output: {expected_rows=} actual={dict(writer.rows_by_survey)}")
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manifest = {
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"schema_version": "1.0", "generated_on": "2026-09-20", "status": "provisional",
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"output_file": str(OUTPUT.relative_to(ROOT)).replace("\\", "/"),
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"sha256": sha256(OUTPUT), "bytes": OUTPUT.stat().st_size,
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"rows": totals[0], "unique_response_keys": totals[1], "item_instances_with_rows": totals[2],
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"rows_by_survey": dict(sorted(writer.rows_by_survey.items())),
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"source_derived_expected_rows": dict(sorted(expected_rows.items())),
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"rows_by_item": dict(sorted(writer.rows_by_item.items())),
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"observed_status_counts": dict(sorted(writer.observed_status.items())),
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"missing_type_counts": dict(sorted(writer.missing_types.items())),
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"required_field_nulls": null_checks[0], "observed_rows_without_canonical_response": null_checks[1],
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"eligibility_rules": {
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"GSHS": "Rows only from the seven components where the primary items were administered.",
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"YRBS": "All respondents in each verified national annual full table; blank source responses remain unknown missing.",
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"NSDUH": "CATAG2=1 (official label: 12-17 years old); only YUSUITHK and YUSUIPLN are locally available.",
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},
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"excluded_item_instances": [
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r["item_version_id"] for r in item_rows
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if r["survey"] == "NSDUH" and r["source_variable"] == "YUSUICTRY"
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],
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"gate_boundary": "No human reviewer fields are inferred. Four NSDUH attempt items have no response rows because the fields are absent from local public-use microdata.",
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}
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MANIFEST.write_text(json.dumps(manifest, indent=2, ensure_ascii=False) + "\n", encoding="utf-8")
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REPORT.write_text(
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"# Primary-outcome response long-table audit\n\n"
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"Status: **provisional; structural validation passed**.\n\n"
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f"- rows: {manifest['rows']:,}\n"
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f"- unique respondent × item keys: {manifest['unique_response_keys']:,}\n"
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f"- item instances with local response data: {manifest['item_instances_with_rows']} of 84\n"
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f"- rows by survey: `{manifest['rows_by_survey']}`\n"
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f"- observed/missing statuses: `{manifest['observed_status_counts']}`\n"
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f"- SHA-256: `{manifest['sha256']}`\n\n"
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"The output row totals equal counts independently derived from the seven GSHS components, all 17 YRBS annual full tables, and NSDUH respondents with CATAG2=1. Required identifiers/status fields are complete, respondent × item keys are unique, and every observed response has a canonical response. The four NSDUH attempt instances remain in the item bank without response rows because the public-use microdata omit those fields. Human double review is still required.\n",
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encoding="utf-8",
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)
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print(json.dumps({k: manifest[k] for k in ["rows", "unique_response_keys", "item_instances_with_rows", "rows_by_survey", "observed_status_counts", "missing_type_counts", "sha256"]}, indent=2))
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if __name__ == "__main__":
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main()
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@@ -10,4 +10,4 @@ Generated from the direct-source registry and audits by `build_primary_outcome_p
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- source conflicts or evidence gaps: 32
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- human reviewers recorded: 0
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The package does not satisfy Gate 1 by itself. Two actual human reviewers must independently sign every primary-outcome item; `responses_long.parquet` is not yet built; NSDUH youth attempt is absent from local public-use microdata; and several design and administered-language fields remain provisional.
|
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The package does not satisfy Gate 1 by itself. `responses_long.parquet` has passed structural validation, but two actual human reviewers must independently sign every primary-outcome item; NSDUH youth attempt is absent from local public-use microdata; and several design and administered-language fields remain provisional.
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@@ -0,0 +1,12 @@
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# Primary-outcome response long-table audit
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Status: **provisional; structural validation passed**.
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- rows: 919,863
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- unique respondent × item keys: 919,863
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- item instances with local response data: 80 of 84
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- rows by survey: `{'GSHS': 64599, 'NSDUH': 91236, 'YRBS': 764028}`
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- observed/missing statuses: `{'data_error': 177, 'dont_know': 458, 'observed': 867995, 'ordinary_missing': 172, 'refused': 6544, 'unknown': 44517}`
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- SHA-256: `0260386444fd2d4a9b0183ef79b171b4fa47ab1d7c1706b05619c14cc8f8a197`
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The output row totals equal counts independently derived from the seven GSHS components, all 17 YRBS annual full tables, and NSDUH respondents with CATAG2=1. Required identifiers/status fields are complete, respondent × item keys are unique, and every observed response has a canonical response. The four NSDUH attempt instances remain in the item bank without response rows because the public-use microdata omit those fields. Human double review is still required.
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@@ -0,0 +1,132 @@
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{
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"schema_version": "1.0",
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"generated_on": "2026-09-20",
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"status": "provisional",
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"output_file": "Dataset/可直接分析数据包_NSDUH_YRBS/harmonization/responses_long.parquet",
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"sha256": "0260386444fd2d4a9b0183ef79b171b4fa47ab1d7c1706b05619c14cc8f8a197",
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"bytes": 4405969,
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"rows": 919863,
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"unique_response_keys": 919863,
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"item_instances_with_rows": 80,
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"rows_by_survey": {
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"GSHS": 64599,
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"NSDUH": 91236,
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"YRBS": 764028
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},
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"source_derived_expected_rows": {
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"GSHS": 64599,
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"NSDUH": 91236,
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"YRBS": 764028
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},
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"rows_by_item": {
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"GSHS::2023_MAR_GSHS_v01::mar_fez2023::raw_mh_attemptsui": 4172,
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"GSHS::2023_MAR_GSHS_v01::mar_fez2023::raw_mh_considersui": 4172,
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"GSHS::2023_MAR_GSHS_v01::mar_fez2023::raw_mh_plansui": 4172,
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"GSHS::GHA_2022_GSHS_v01::gha_sek_tak2022::raw_mh_attemptsui": 3796,
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"GSHS::GHA_2022_GSHS_v01::gha_sek_tak2022::raw_mh_considersui": 3796,
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"GSHS::GHA_2022_GSHS_v01::gha_sek_tak2022::raw_mh_plansui": 3796,
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"GSHS::IND_2022_GSHS_v01::ind_jaipur_2022::raw_mh_attemptsui": 4299,
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"GSHS::IND_2022_GSHS_v01::ind_jaipur_2022::raw_mh_considersui": 4299,
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"GSHS::IND_2022_GSHS_v01::ind_jaipur_2022::raw_mh_plansui": 4299,
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"GSHS::JAM_2023_GSHS_v01::jam_st_cath_2023::raw_mh_attemptsui": 3041,
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"GSHS::JAM_2023_GSHS_v01::jam_st_cath_2023::raw_mh_considersui": 3041,
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"GSHS::JAM_2023_GSHS_v01::jam_st_cath_2023::raw_mh_plansui": 3041,
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"GSHS::MNG_2023_GSHS_v01::mng2023::raw_mh_attemptsui": 3311,
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"GSHS::MNG_2023_GSHS_v01::mng2023::raw_mh_considersui": 3311,
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"GSHS::MNG_2023_GSHS_v01::mng2023::raw_mh_plansui": 3311,
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"GSHS::SLB_2023_GSHS_v01::slb_2023::raw_mh_attemptsui": 1995,
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"GSHS::SLB_2023_GSHS_v01::slb_2023::raw_mh_considersui": 1995,
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"GSHS::SLB_2023_GSHS_v01::slb_2023::raw_mh_plansui": 1995,
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"GSHS::WLF_2023_GSHS_v01::wlf_2023::raw_mh_attemptsui": 919,
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"GSHS::WLF_2023_GSHS_v01::wlf_2023::raw_mh_considersui": 919,
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"GSHS::WLF_2023_GSHS_v01::wlf_2023::raw_mh_plansui": 919,
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"NSDUH::2021::YUSUIPLN": 10743,
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"NSDUH::2021::YUSUITHK": 10743,
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||||
"NSDUH::2022::YUSUIPLN": 11969,
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"NSDUH::2022::YUSUITHK": 11969,
|
||||
"NSDUH::2023::YUSUIPLN": 11572,
|
||||
"NSDUH::2023::YUSUITHK": 11572,
|
||||
"NSDUH::2024::YUSUIPLN": 11334,
|
||||
"NSDUH::2024::YUSUITHK": 11334,
|
||||
"YRBS::1991::Q19": 12272,
|
||||
"YRBS::1991::Q20": 12272,
|
||||
"YRBS::1991::Q21": 12272,
|
||||
"YRBS::1993::Q24": 16296,
|
||||
"YRBS::1993::Q25": 16296,
|
||||
"YRBS::1993::Q26": 16296,
|
||||
"YRBS::1995::Q22": 10904,
|
||||
"YRBS::1995::Q23": 10904,
|
||||
"YRBS::1995::Q24": 10904,
|
||||
"YRBS::1997::Q22": 16263,
|
||||
"YRBS::1997::Q23": 16263,
|
||||
"YRBS::1997::Q24": 16263,
|
||||
"YRBS::1999::Q23": 15349,
|
||||
"YRBS::1999::Q24": 15349,
|
||||
"YRBS::1999::Q25": 15349,
|
||||
"YRBS::2001::Q24": 13601,
|
||||
"YRBS::2001::Q25": 13601,
|
||||
"YRBS::2001::Q26": 13601,
|
||||
"YRBS::2003::Q24": 15214,
|
||||
"YRBS::2003::Q25": 15214,
|
||||
"YRBS::2003::Q26": 15214,
|
||||
"YRBS::2005::Q24": 13917,
|
||||
"YRBS::2005::Q25": 13917,
|
||||
"YRBS::2005::Q26": 13917,
|
||||
"YRBS::2007::Q24": 14041,
|
||||
"YRBS::2007::Q25": 14041,
|
||||
"YRBS::2007::Q26": 14041,
|
||||
"YRBS::2009::Q24": 16410,
|
||||
"YRBS::2009::Q25": 16410,
|
||||
"YRBS::2009::Q26": 16410,
|
||||
"YRBS::2011::Q25": 15425,
|
||||
"YRBS::2011::Q26": 15425,
|
||||
"YRBS::2011::Q27": 15425,
|
||||
"YRBS::2013::Q27": 13583,
|
||||
"YRBS::2013::Q28": 13583,
|
||||
"YRBS::2013::Q29": 13583,
|
||||
"YRBS::2015::Q27": 15624,
|
||||
"YRBS::2015::Q28": 15624,
|
||||
"YRBS::2015::Q29": 15624,
|
||||
"YRBS::2017::Q26": 14765,
|
||||
"YRBS::2017::Q27": 14765,
|
||||
"YRBS::2017::Q28": 14765,
|
||||
"YRBS::2019::Q26": 13677,
|
||||
"YRBS::2019::Q27": 13677,
|
||||
"YRBS::2019::Q28": 13677,
|
||||
"YRBS::2021::Q26": 17232,
|
||||
"YRBS::2021::Q27": 17232,
|
||||
"YRBS::2021::Q28": 17232,
|
||||
"YRBS::2023::Q27": 20103,
|
||||
"YRBS::2023::Q28": 20103,
|
||||
"YRBS::2023::Q29": 20103
|
||||
},
|
||||
"observed_status_counts": {
|
||||
"data_error": 177,
|
||||
"dont_know": 458,
|
||||
"observed": 867995,
|
||||
"ordinary_missing": 172,
|
||||
"refused": 6544,
|
||||
"unknown": 44517
|
||||
},
|
||||
"missing_type_counts": {
|
||||
"data_error": 177,
|
||||
"dont_know": 458,
|
||||
"ordinary_missing": 172,
|
||||
"refused": 6544,
|
||||
"unknown": 44517
|
||||
},
|
||||
"required_field_nulls": 0,
|
||||
"observed_rows_without_canonical_response": 0,
|
||||
"eligibility_rules": {
|
||||
"GSHS": "Rows only from the seven components where the primary items were administered.",
|
||||
"YRBS": "All respondents in each verified national annual full table; blank source responses remain unknown missing.",
|
||||
"NSDUH": "CATAG2=1 (official label: 12-17 years old); only YUSUITHK and YUSUIPLN are locally available."
|
||||
},
|
||||
"excluded_item_instances": [
|
||||
"NSDUH::2021::YUSUICTRY",
|
||||
"NSDUH::2022::YUSUICTRY",
|
||||
"NSDUH::2023::YUSUICTRY",
|
||||
"NSDUH::2024::YUSUICTRY"
|
||||
],
|
||||
"gate_boundary": "No human reviewer fields are inferred. Four NSDUH attempt items have no response rows because the fields are absent from local public-use microdata."
|
||||
}
|
||||
Reference in New Issue
Block a user