QuantCrit Core Principles
This idea stresses that researchers’ choices shape the data and outcomes.
What is "data cannot speak for itself"?
This historical sociologist challenged racial biases in early social science by emphasizing systemic analysis.
Who is W. E. B. Du Bois?
The process of defining abstract concepts as measurable variables reflects these researcher-driven decisions.
What is "operationalization"?
According to QuantCrit, these choices significantly shape research outcomes but are often hidden.
What are "Methodological choices"?
QuantCrit challenges this traditional assumption about numbers in research.
What is "Numbers are neutral"?
The authors critique this research practice, which treats race as a fixed, unchanging variable.
What is "Reifying race"?
A belief that numbers alone can reveal the truth.
What is "The myth of objectivity"?
QuantCrit encourages researchers to write this to reflect on how their identity shapes their work.
What is "A positionality statement"?
This principle focuses on the need for research to address systemic inequities.
What is "a social justice orientation"?
Statistical practices that average data obscure systemic inequities.
What is "the problem of aggregation"?
The use of statistical analysis was historically shaped by this pseudo-scientific ideology.
What is "Eugenics"?
The decision to include or exclude certain groups or variables reflects this type of methodological bias.
What is selection bias?