Quantitative Methodology Research: Is it on Psychologists’ Reading Lists?
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
Two studies investigated the extent to which researchers are accessing quantitative \nmethodology publications. The first study investigated the number of references to \nquantitative methodology sources in research articles from six prominent psychology \njournals. The analyses revealed that 39% of all articles reviewed did not include a \nquantitative reference of any kind and that 72% contained two or fewer. The second \nstudy targeted publications in quantitative methodology journals to determine the \nfrequency with which they were being referenced in non-quantitative publications and \nother quantitative methodology publications. Results indicate that quantitative methodology articles are being referenced equally by non-quantitative and quantitative methodology researchers, but more importantly, that the number of references to quantitative methodology articles is very low. The results of these studies suggest that researchers are diligent in determining research protocol, procedures, and best practices within their own field, but that researchers are not frequently accessing the quantitative methodology literature to determine the best way to analyze their data. Alternatively, researchers might indeed invest time into determining recent and best statistical procedures, but do not indicate so in the reference section of their work; if this is the case then this paper should be a strong reminder to psychologists about referencing the statistical approaches they utilize.
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 | 0.666 | 0.626 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.004 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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