Decline and Fall, Growth and Spread, or Resilience? Approaches to Studying How and Why Societies Change
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
An avid reader of history will be quite familiar with the rich, emotive narratives detailing the tragic decline and ultimate fall of once mighty civilizations; Rome succumbing to barbarian hordes, Alexander of Macedon’s and Chinggis Khan’s spear-won empires splitting into warring factions, and the demise of the great Inca or Maya civilizations are just a few such examples. On the other side of the stacks, similarly grandiose narratives document some group’s incredible growth and spread taking over vast territories and populations. These tell typically of societies coming to dominate a region, often in the face of overwhelming odds and tribulation or through some precocious development of a key technology or strategy that later becomes widespread. Here, I take stock of previous approaches to studying function – from growth and development to crisis and collapse to resilience – and ask what is the most fruitful lens with which to view fluctuations in how societies function and change over time, as this review essay attempts to accomplish.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| 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 it