Bibliographic record
Abstract
Commentators frequently observe that the pace of social change accelerated during the 20th century. Processes of industrialization, demographic change, and human-induced environmental change all occurred more rapidly at the end of the century than they did at the beginning. While claims about accelerating social change abound, few studies attempt to explain it. This article tries to do so through a quantitative analysis of the changing pace of fertility declines over the past two centuries. It outlines two possible explanations for the acceleration: a social integration thesis which emphasizes our growing interconnectivity; and a ‘latecomer effect’ which attributes the accelerated processes to political efforts by elites in poorer countries who want to ‘catch up’ with more affluent countries. An empirical analysis of fertility declines provides support for both explanations. Increased social integration through the spread of common languages may have facilitated the transmission of new norms about fertility, and the creation of elite initiated family planning programs after the Second World War expanded access to contraceptives.!
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 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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.005 | 0.014 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.015 | 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 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".