Клод М. Стил

Как стереотипы заставляют мозг тупеть


Скачать книгу

исследованиях это окажется лишним. Сильные студенты-математики женского пола отставали в тестах вроде этого без напоминания, что в нем проявляются гендерные различия. Они просто предполагали это.

      8

      Daryl Michael Scott Contempt and Pity

      9

      Важно подчеркнуть, что мы использовали стандартные статистические процедуры, чтобы подогнать результаты наших «черных» и белых студентов под любые различия в навыках решения тестов (основываясь на их результатах АОТ при поступлении), которые могли существовать между черными и белыми студентами до эксперимента. Это позволило нам для всех целей и намерений отобрать «черных» и белых участников с одинаковыми навыками и знаниями в решении тестов.

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