Thinking About Measures and Measurement in Positivist Research: A Proposal for Refocusing on Fundamentals
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We challenge two taken-for-granted assumptions about measurement in positivist research. The first assumption is that measures and measurements are relevant for quantitative, but not qualitative, research. We explain why they apply to both types of research. The second assumption we challenge is that existing measurement practices are unproblematic, even if researchers sometimes vary in how well they enact them. We explain why current norms (both espoused and enacted) are deficient in some important ways because they fail to emphasize the fundamental issues of measures and measurements. Drawing on symbolic logic, we provide a framework to help positivist researchers to assess efforts in measuring and measurement regardless of their quantitative or qualitative orientation. The framework provides more parsimonious and broadly applicable guidance than available to date and suggests the need to refocus on measurement fundamentals. The online appendix is available at https://doi.org/10.1287/isre.2017.0704 .
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.105 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it