When theories become tools: Toward a framework for pragmatic validity
Bibliographic record
Abstract
In this article we discuss the characteristics of knowledge that lead to practical utility. We first review previous efforts at identifying the characteristics of useful knowledge. These contributions are grouped into three perspectives according to which representational mode they imply: propositional, narrative, or visual. We develop a framework for pragmatic validity that encompasses knowledge represented in all three modes. However, we also note an over-reliance on the propositional mode in academia, which contrasts with a preference for narrative and visual knowledge among practitioners. Explicit and propositional knowledge are key criteria for achieving scientific validity, but more ambiguous knowledge serves important functions in organizational life and may thus possess pragmatic validity. We highlight the role of conceptual models expressed in a visual format, a representational mode that has received little attention in the literature. We end with suggestions for further research that may extend the notion of pragmatic validity and lead to a more refined framework for the development of useful knowledge.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.157 | 0.227 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.014 | 0.006 |
| Science and technology studies | 0.012 | 0.139 |
| Scholarly communication | 0.033 | 0.076 |
| Open science | 0.007 | 0.024 |
| Research integrity | 0.015 | 0.015 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".