WGEA Headline Gender Pay Gap - mid-point of employer gaps, by ANZSIC division (annual)

The headline industry-level gender pay gap percentages WGEA publishes in its annual Employer Gender Pay Gaps Report. One row per ANZSIC division (19 divisions) plus a synthetic "All employers" national row - fetched from the official WGEA spreadsheet, aggregated server-side to a small agent-friendly response (~20 rows × 5 measures). Answers the most-searched WGEA question - "what's Australia's gender pay gap?" / "what's the pay gap in mining?" - in a single call. The other seven WGEA curated datasets are per-employer questionnaire responses; none of them carry the rolled-up industry pay-gap percentage because WGEA aggregates remuneration data BEFORE publishing the per-employer CSVs. Methodology - three flavours of GPG so you can pick the one that matches your question: HEADLINE_GAP measures ───────────────────── `employee_weighted_total_rem_gap_pct` / `_base_salary_...` ⭐ This is WGEA's published "Mean Total Remuneration GPG" (~21.1% for 2024-25 All-employers). Workforce-weighted: each employee contributes equally, derived from the employer's % women + average pay + size band. Reproduces WGEA's Scorecard headline within ~0.6pp. USE THIS for "Australia's gender pay gap" headline comparisons. `total_remuneration_gap_pct` / `base_salary_gap_pct` = mean of per-employer "Average ... GPG (%)" - unweighted, one employer one vote. Lower than the employee-weighted figure because most employers are small and small employers have smaller absolute pay gaps. `median_total_rem_gap_pct` / `median_base_salary_gap_pct` = median of per-employer "Median ... GPG (%)" - the typical (middle) employer's gap. Strips outliers. What HEADLINE_GAP IS useful for ────────────────────────────── - WGEA-headline-style national + per-industry GPG comparisons (use the employee_weighted measures) - "Typical employer's gap" in industry X (use the median measures) - Outlier-employer detection (compare mean vs median measures) - Tracking the same measure over reporting years Notes: - Percentages are out of 100 (so 21.4 = 21.4%, NOT 0.214). - Filter `anzsic_division` is permissive - pass the full division name ('Mining', 'Financial and Insurance Services'), the canonical letter ('B', 'K'), or 'All employers' for the national row. - Source xlsx is fetched directly from wgea.gov.au (not data.gov.au - WGEA does not publish the aggregated spreadsheet to CKAN; only the per-employer questionnaire CSVs land there).