统计不是测量:心理测量尺度和基于语言的模型的内置语义掩盖了关键的认识论差异
1School of Human Sciences, University of Greenwich, London, United Kingdom.
Frontiers in psychology
|July 11, 2025
概括
心理学过度强调统计模型,忽视了适当的测量. 这导致实用量化,缺乏对现象的真正理解,阻碍了科学进步,并使该领域的危机持续存在.
科学领域:
- 心理学 心理学 心理学
- 科学哲学的哲学科学哲学
- 测量科学 测量科学 测量科学
背景情况:
- 心理学在很大程度上依赖于统计建模,往往忽视了认识论上正确测量的基本原则.
- 结构关系的统计分析与测量之间存在一个关键的区别,这种测量建立了现象和数据之间的经验联系.
- 现有的测量模型,如罗森的测量模型,为理解这些关系提供了框架,这对于科学严谨性至关重要.
研究的目的:
- 批评心理学过度依赖统计建模而牺牲认识论基础的测量.
- 详细阐述心理学在建立真正的测量类比方面所面临的认识挑战.
- 在心理学研究中提出一条通向认识论上合理的推断的道路.
主要方法:
- 批评心理学当前的统计实践.
- 在心理学研究中应用罗森的一般测量模型.
- 对认识系统循环性的计量方法的分析 (协调,校准).
- 检查心理现象 (复杂性,非ergodicity) 和基于语言的方法所带来的挑战.
- 探索人工智能 (AI) 用于自然语言分析.
主要成果:
- 心理测量学未能建立协调和校准的测量关系,只能产生务实的量化.
- 心理学家经常将方法语义与现象混为一谈,模糊了本体学和认识论的区别.
- 统计无法确定或分析模型与研究现象的关系.
- 人工智能驱动的自然语言处理 (NLP) 提供了分析不受限制的口头反应的潜力.
结论:
- 心理学当前的方法导致了认识学上的差距,阻碍了真正的理解,并延续了"根本错误".
- 经验学上合理的推断需要方法来弥合正式模型和经验现象之间的差距.
- 虽然人工智能提供了新的可能性,但其用于生成标准化描述的滥用可能会加剧现有的问题.
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