This approach requires sourcing and maintaining accurate information, which means you can't fabricate numbers or exaggerate metrics. AI models increasingly cross-reference claims across sources, and inconsistencies damage credibility. The data you include must be truthful and, where relevant, attributed to primary sources. But when you consistently provide specific, accurate information, you build a reputation as a reliable source that AI models return to repeatedly.
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Structural racism and persistent inequalities leading to "notably higher risk of adverse outcomes" for women from black and Asian backgrounds and women from more deprived areas. Discrimination against disabled women, Muslim families, refugee and asylum women and LGBT families was also reported
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