Amplifying issues related to psychological testing and assessment.
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
February 2002 • American Psychologist able to improve on the validity of their assessment conclusions (Garb, 1998; Grove, Zald, Lebow, Snitz, & Nelson, 2000). Because Meyer et al. (2001) provided an overly optimistic evaluation of current psychological assessment practices, many readers of their article are likely to conclude that the scientific status of psychological assessment is firmly established. Unfortunately, nothing could be further from the truth. A more accurate conclusion is that very little is known about the validity or utility of psychological assessment. This does not mean that psychological assessment is without merit; rather, it indicates that, as with so many aspects of psychological practice, psychologists lack scientific evidence that bears on assessment’s value. Psychologists must build a science of assessment, not just a body of research on tests and test subscales. If psychological assessment is to be promoted on the basis of science, it must be on the basis of relevant studies of assessment, not on unwarranted extrapolations from the literature on test validity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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