Forms and Functions of the Social Emotions
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
In engineering, form follows function. It is therefore difficult to understand an engineered object if one does not examine it in light of its function. Just as understanding the structure of a lock requires understanding the desire to secure valuables, understanding structures engineered by natural selection, including emotion systems, requires hypotheses about adaptive function. Social emotions reliably solved adaptive problems of human sociality. A central function of these emotions appears to be the recalibration of social evaluations in the minds of self and others. For example, the anger system functions to incentivize another individual to value your welfare more highly when you deem the current valuation insufficient; gratitude functions to consolidate a cooperative relationship with another individual when there are indications that the other values your welfare; shame functions to minimize the spread of discrediting information about yourself and the threat of being devalued by others; and pride functions to capitalize on opportunities to become more highly valued by others. Using the lens of social valuation, researchers are now mapping these and other social emotions at a rapid pace, finding striking regularities across industrial and small-scale societies and throughout history.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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