Reductionist vs Nonreductionist Conceptualizations of Psychological and Social Measurement

Reductionist

  • Root metaphor: Mechanical clockwork universe
  • Paradigmatic case: Newtonian physics
  • Complete, consistent, deterministic structures
  • Whole is sum of parts
  • Sufficient statistics: Mean & std deviation
  • Uncertainty is variation across repeated measures
  • Test/survey items in use define totality of universe of possibility; changes in items change that universe
  • Descriptive, reactionary
  • Microlevel facts are supposed to additively combine into general laws
  • General laws are discovered by measuring
  • Top down data analytics influence policy
  • Externally imposed assembly processes
  • Subject/object dualism institutionalized in data analytics process
  • Data are hallmark criterion of objectivity
  • Subjectivity discounted, removed if possible
  • Counts are quantities
  • Ordinal scores treated as interval measures with no justification
  • Score variation relates solely to person characteristics
  • Score meaning tied to particular questions asked
  • Quantitative methods don’t define unit quantities or test for them
  • Qualitative data and methods are separated from quantitative data/methods
  • No model of construct stated or tested
  • Group level multivariate focus
  • P-values are primary model fit criterion
  • Population sampling motivates probabilistic approach
  • Equating based on statistical assumptions concerning score distribution

Nonreductionist

  • Root metaphor: Living organic universe
  • Paradigmatic case: Multilevel ecosystems
  • Incomplete, not perfectly consistent, stochastic structures
  • Whole is greater than sum of parts
  • Sufficient statistics: scores
  • Uncertainty is resonance of stochastic invariance within individual measures
  • Test/survey items in use sample from infinite population; changes in items used do not change that universe
  • Prescriptive, anticipatory
  • Microlevel facts self-organize into meso abstractions & macro formalisms
  • Measuring presumes general laws
  • Bottom up alignments and coordinations of decisions and behaviors move society
  • Internal processes of self-organization
  • Mutually implied subject-object entangled together in playful flow institutionalized via distributed instrumentation
  • Objectivity requires data explained by theory embodied in instruments
  • Subjectivity included as valid source of concerns and insights scrutinized for value
  • Counts might lead to quantity definition
  • Interval measures theoretically and empirically substantiated
  • Empirical & theoretical measure variation maps construct via items and persons
  • Measure meaning is independent of particular questions asked
  • Quantitative methods define unit quantities and test for them
  • Qualitative methods are integrated with quantitative methods
  • Mathematical, observation, and construct models stated and tested
  • Individual level univariate focus
  • Meaningful construct definition primary model fit criterion
  • Individual response process motivates probabilistic approach
  • Equating requires alignment of items along common dimension

 

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