Historical time in the age of big data: Cultural psychology, historical change, and the Google Books Ngram Viewer.
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
Launched in 2010, the Google Books Ngram Viewer offers a novel means of tracing cultural change over time. This digital tool offers exciting possibilities for cultural psychology by rendering questions about variation across historical time more quantitative. Psychologists have begun to use the viewer to bolster theories about a historical shift in the United States from a more collectivist to individualist form of selfhood and society. I raise 4 methodological cautions about the Ngram Viewer's use among psychologists: (a) the extent to which print culture can be taken to represent culture as a whole, (b) the difference between viewing the past in terms of trends versus events, (c) assumptions about the stability of a word's meaning over time, and (d) inconsistencies in the scales and ranges used to measure change over time. The aim is to foster discussion about the standards of evidence needed for incorporating historical big data into empirical research.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it