Between Pink Noise and White Noise: A Digital History of <i>The American Journal of Psychology</i> and <i>Psychological Review</i>
Bibliographic record
Abstract
Abstract The frequency with which authors contribute to The American Journal of Psychology (AJP) or Psychological Review (PR) is analyzed from the inceptions of both journals (1887 for AJP and 1894 for PR) until 2015. In the beginning, a small number of authors tend to make a large percentage of contributions, but this percentage shrinks over time. The slopes of the author distributions for each journal start out close to -1 (pink noise) and then gradually drift toward 0 (white noise). This means that the distributions flatten as the authors become more diverse, which in turn changes the experience of reading the journals. An explanation of these findings focuses on two factors. One is an increase in the amount of congestion as the number of authors grows ever larger. The other is a decline in the cohesiveness of the community of authors.
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.
How this classification was reachedexpand
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 | 0.018 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.000 | 0.009 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.006 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".