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
The emotion of pride appears to be a neurocognitive guidance system to capitalize on opportunities to become more highly valued and respected by others. Whereas the inputs and the outputs of pride are relatively well understood, little is known about how the pride system matches inputs to outputs. How does pride work? Here we evaluate the hypothesis that pride magnitude matches the various outputs it controls to the present activating conditions - the precise degree to which others would value the focal individual if the individual achieved a particular achievement. Operating in this manner would allow the pride system to balance the competing demands of effectiveness and economy, to avoid the dual costs of under-deploying and over-deploying its outputs. To test this hypothesis, we measured people's responses regarding each of 25 socially valued traits. We observed the predicted magnitude matchings. The intensities of the pride feeling and of various motivations of pride (communicating the achievement, demanding better treatment, investing in the valued trait and pursuing new challenges) vary in proportion: (a) to one another; and (b) to the degree to which audiences value each achievement. These patterns of magnitude matching were observed both within and between the USA and India. These findings suggest that pride works cost-effectively, promoting the pursuit of achievements and facilitating the gains from others' valuations that make those achievements worth pursuing.
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 | 0.000 |
| 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) | 0.004 | 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