The Genetic and the Sociological: Exploring the Possibility of Consilience
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
We argue that consilience, or the unity of all knowledge, is an important goal for all researchers to pursue. The philosophical foundations of this position are explored, and then an empirical study is presented that illustrates what could be gained by melding behaviour genetic, sociological and other perspectives on politics. Twin data are analysed to examine the extent to which sociological factors can explain the variation in three dependent variables: left/liberal versus right/conservative political orientations; party identification; and interest in politics. The results indicate that large amounts of the variance in these variables are not explained by the sociological predictors, so the residual variance is tested for genetic influences, which yields fairly high heritability estimates. We conclude that analyses that are informed by both genetic and sociological insights are essential for understanding the phenomena examined, and explore the implications of this conclusion for conventional research paradigms and for consilience.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.011 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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