feat(compare): academics strips with England anchors and More measures
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_0146VHeLAWjDVE2B5uU67jCB
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/**
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* How children do academically — tier-1 dot strips anchored on official
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* England averages, tier-2 "More measures" one tap away, equity row against
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* the computed state-school benchmark. Copy verbatim from the reviewed
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* mockups; teacher-assessed measures are labelled as such.
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*/
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'use client';
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import { latestValues, verdict } from '@/lib/compareLogic';
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import type { Benchmarks, ComparisonData, NationalAverages, School } from '@/lib/types';
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import { DotStrip } from '@/components/DotStrip';
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import { Cell, Chip, RowLabel, Section, SectionGrid, sectionStyles as s } from './sectionShared';
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import styles from './CompareAcademics.module.css';
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interface StripSpec {
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label: string;
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metric: string;
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anchorKey?: string;
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tip?: string;
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min?: number;
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max?: number;
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unit?: string;
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}
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const TIER1_PRIMARY: StripSpec[] = [
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{
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label: 'Reading, writing & maths — expected standard',
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metric: 'rwm_expected_pct',
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anchorKey: 'rwm_expected_pct',
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tip: '% of Year 6 pupils reaching the expected standard in reading, writing and maths.',
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},
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{ label: 'Reading', metric: 'reading_expected_pct', anchorKey: 'reading_expected_pct' },
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{
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label: 'Writing (teacher-assessed)',
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metric: 'writing_expected_pct',
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anchorKey: 'writing_expected_pct',
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tip: 'Writing is assessed by teachers, not tested.',
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},
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{ label: 'Maths', metric: 'maths_expected_pct', anchorKey: 'maths_expected_pct' },
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{
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label: 'Working at a higher standard than expected',
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metric: 'rwm_high_pct',
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anchorKey: 'rwm_high_pct',
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tip: 'A high score in the reading and maths tests plus “greater depth” in teacher-assessed writing.',
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},
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];
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const TIER2_PRIMARY: StripSpec[] = [
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{
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label: 'Grammar, punctuation & spelling — expected standard',
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metric: 'gps_expected_pct',
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anchorKey: 'gps_expected_pct',
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},
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{
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label: 'Science — expected standard (teacher-assessed)',
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metric: 'science_expected_pct',
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anchorKey: 'science_expected_pct',
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tip: 'Teacher-assessed, like writing — there has been no KS2 science test since 2009, so comparisons are indicative.',
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},
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{
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label: 'Average scaled score — reading',
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metric: 'reading_avg_score',
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anchorKey: 'reading_avg_score',
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min: 100,
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max: 120,
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unit: '',
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},
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{
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label: 'Average scaled score — maths',
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metric: 'maths_avg_score',
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anchorKey: 'maths_avg_score',
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min: 100,
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max: 120,
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unit: '',
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},
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{
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label: 'Average scaled score — grammar, punctuation & spelling',
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metric: 'gps_avg_score',
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anchorKey: 'gps_avg_score',
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min: 100,
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max: 120,
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unit: '',
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},
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];
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function Strip({
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spec,
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data,
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urns,
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schoolNames,
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national,
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}: {
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spec: StripSpec;
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data: Record<string, ComparisonData>;
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urns: number[];
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schoolNames: string[];
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national: Record<string, number> | undefined;
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}) {
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const values = latestValues(data, urns, spec.metric).map((v) =>
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v != null ? Math.round(v) : null,
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);
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const anchorValue = spec.anchorKey ? national?.[spec.anchorKey] : undefined;
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const anchor =
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anchorValue != null
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? { value: anchorValue, label: `England ${Math.round(anchorValue)}${spec.unit ?? '%'}` }
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: null;
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if (values.every((v) => v == null)) return null;
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return (
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<DotStrip
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label={spec.label}
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values={values}
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schoolNames={schoolNames}
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anchor={anchor}
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min={spec.min ?? 0}
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max={spec.max ?? 100}
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unit={spec.unit ?? '%'}
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tip={spec.tip}
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/>
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);
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}
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export function CompareAcademics({
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schools,
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data,
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nationalAverages,
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benchmarks,
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}: {
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schools: School[];
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data: Record<string, ComparisonData>;
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nationalAverages?: NationalAverages;
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benchmarks?: Benchmarks;
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}) {
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const urns = schools.map((school) => school.urn);
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const schoolNames = schools.map((school) => school.school_name);
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const isSecondary = schools.some(
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(school) => data[String(school.urn)]?.school_info?.attainment_8_score != null,
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);
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if (isSecondary) {
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const att8 = latestValues(data, urns, 'attainment_8_score');
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const banding = urns.map((urn) => {
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const rows = data[String(urn)]?.yearly_data ?? [];
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for (let i = rows.length - 1; i >= 0; i--) {
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if (rows[i].progress_8_banding) return rows[i].progress_8_banding as string;
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}
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return null;
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});
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const grade5 = latestValues(data, urns, 'english_maths_strong_pass_pct');
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const ebacc = latestValues(data, urns, 'ebacc_entry_pct');
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const att8Anchor = nationalAverages?.secondary?.attainment_8_score;
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return (
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<Section
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title="How students do academically"
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how="GCSE results (latest year). Attainment 8 averages performance across eight subjects; Progress 8 shows how much progress students make compared with similar students nationally — the wording is DfE's own banding."
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>
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<SectionGrid schools={schools}>
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<RowLabel tip="Average Attainment 8 score across eight GCSE subjects.">Attainment 8</RowLabel>
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{schools.map((school, i) => (
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<Cell key={school.urn} school={school} index={i}>
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{att8[i] != null ? (
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<>
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<span className={s.big}>{(att8[i] as number).toFixed(1)}</span>
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{att8Anchor != null && (
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<span className={s.small}>England average {att8Anchor.toFixed(1)}</span>
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)}
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</>
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) : (
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<span className={s.small}>No data</span>
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)}
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</Cell>
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))}
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<RowLabel tip="DfE's own plain-English Progress 8 label.">Progress 8</RowLabel>
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{schools.map((school, i) => (
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<Cell key={school.urn} school={school} index={i}>
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{banding[i] ? (
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<Chip
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tone={
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/well above|above/i.test(banding[i] as string)
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? 'good'
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: /well below|below/i.test(banding[i] as string)
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? 'warn'
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: 'neutral'
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}
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>
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{banding[i]}
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</Chip>
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) : (
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<span className={s.small}>No data</span>
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)}
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</Cell>
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))}
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<RowLabel tip="% achieving grade 5 or above in both English and maths GCSEs.">
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Grade 5+ in English & maths
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</RowLabel>
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{schools.map((school, i) => (
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<Cell key={school.urn} school={school} index={i}>
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{grade5[i] != null ? `${Math.round(grade5[i] as number)}%` : <span className={s.small}>No data</span>}
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</Cell>
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))}
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<RowLabel tip="% entering the English Baccalaureate subject combination.">EBacc entry</RowLabel>
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{schools.map((school, i) => (
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<Cell key={school.urn} school={school} index={i}>
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{ebacc[i] != null ? `${Math.round(ebacc[i] as number)}%` : <span className={s.small}>No data</span>}
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</Cell>
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))}
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</SectionGrid>
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</Section>
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);
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}
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const national = nationalAverages?.primary;
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const disadvantaged = latestValues(data, urns, 'rwm_expected_disadvantaged_pct');
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const disadvantagedAnchor = benchmarks?.primary?.disadvantaged_rwm_expected_pct ?? null;
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return (
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<Section
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title="How children do academically"
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how="Results from national tests and teacher assessments at the end of Year 6 — writing is assessed by teachers, not tested. Each line runs from 0–100%; the grey tick marks the England average, so dots to its right are above average."
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>
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<div className={s.card}>
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{TIER1_PRIMARY.map((spec) => (
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<Strip
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key={spec.metric}
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spec={spec}
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data={data}
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urns={urns}
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schoolNames={schoolNames}
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national={national}
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/>
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))}
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<details className={styles.moreMeasures}>
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<summary>More measures — grammar, punctuation & spelling, science, average scaled scores</summary>
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{TIER2_PRIMARY.map((spec) => (
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<Strip
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key={spec.metric}
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spec={spec}
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data={data}
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urns={urns}
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schoolNames={schoolNames}
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national={national}
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/>
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))}
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<p className={styles.stripNote}>
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The scaled-score strips show the 100–120 window of the full 80–120 range; 100 is the
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expected standard. Where an England tick is missing, the official figure isn't in
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our dataset yet.
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</p>
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</details>
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</div>
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{disadvantaged.some((v) => v != null) && (
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<SectionGrid schools={schools}>
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<RowLabel tip="% of disadvantaged pupils (free school meals in the last 6 years, or looked after by the local authority) reaching the expected standard. Benchmark computed across state schools in our dataset. Based on smaller pupil groups, so a single pupil can move a school's figure noticeably.">
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Children from lower-income families
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</RowLabel>
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{schools.map((school, i) => {
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const value = disadvantaged[i];
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return (
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<Cell key={school.urn} school={school} index={i}>
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{value != null ? (
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<>
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<span className={s.big} style={{ fontSize: '1.1rem' }}>
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{Math.round(value)}%
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</span>{' '}
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{disadvantagedAnchor != null && (
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<Chip tone={verdict(value, disadvantagedAnchor, 5) === 'below' ? 'warn' : 'good'}>
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{verdict(value, disadvantagedAnchor, 5) === 'above' &&
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`Well above the ${Math.round(disadvantagedAnchor)}% state-school average`}
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{verdict(value, disadvantagedAnchor, 5) === 'close' &&
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`Around the ${Math.round(disadvantagedAnchor)}% state-school average`}
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{verdict(value, disadvantagedAnchor, 5) === 'below' &&
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`Below the ${Math.round(disadvantagedAnchor)}% state-school average`}
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</Chip>
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)}
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</>
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) : (
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<span className={s.small}>No data</span>
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)}
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</Cell>
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);
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})}
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</SectionGrid>
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)}
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</Section>
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);
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}
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