Big Gods and big science: further reflections on theory, data, and analysis
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
Our target article empirically tested the Big Gods Hypothesis which proposes that beliefs in moralizing supernatural punishment (MSP) contributed to the evolution of socio-political complexity (SPC) in world history. We tested this hypothesis using a suite of measures of MSP, SPC, and other potential evolutionary drivers coded in Seshat: Global History Databank. Our analyses indicate that intensity of warfare and productivity of agriculture were major drivers in the evolution of both SPC and MSP. The correlation between social complexity and moralizing religion resulted from shared evolutionary drivers, rather than from direct causal relationships between these two variables. Most commentaries on the target article broadly accept our conclusions, but some argue that alternative measures might be used in future studies before the Big Gods Hypothesis can be conclusively rejected. In this response, we argue that while some of these alternative measures should be developed, they are closely related to the ones we have already adopted. Thus, it seems unlikely that further research will give rise to substantially different outcomes. A particularly fruitful aspect of the discussion is that it illustrates both the pitfalls and productive affordances of transdisciplinary research that seeks to bridge the “two cultures” of the humanities and sciences.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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