Validity in the Next Era of Assessment: Consequences, Social Impact, and Equity
Bibliographic record
Abstract
Validity has long held a venerated place in education, leading some authors to refer to it as the "sine qua non" or "cardinal virtue" of assessment. And yet, validity has not held a fixed meaning; rather it has shifted in its definition and scope over time. In this Eye Opener, the authors explore if and how current conceptualizations of validity fit a next era of assessment that prioritizes patient care and learner equity. They posit that health profession education's conceptualization of validity will change in three related but distinct ways. First, consequences of assessment decisions will play a central role in validity arguments. Second, validity evidence regarding impacts of assessment on patients and society will be prioritized. Third, equity will be seen as part of validity rather than an unrelated concept. The authors argue that health professions education has the agency to change its ideology around validity, and to align with values that predominate the next era of assessment such as high-quality care and equity for learners and patients.
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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 | 0.189 | 0.251 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.010 | 0.201 |
| Scholarly communication | 0.031 | 0.040 |
| Open science | 0.004 | 0.028 |
| Research integrity | 0.012 | 0.016 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".