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
This paper examines feelings and emotions in relation to entertainment experiences. Feelings reflect an appraisal of everyday events or media products that shape our experience of pleasure and interest which are complementary. Pleasure can result from the meaningful interpretation of a program or from positive associations that it evokes. Interest in a program can result from intellectual engagement and a search for meaning or simply to alleviate boredom. According to a reactive model of media involvement, a person selects stimuli which modulate feelings of pleasure or excitement. This affective covariation process is superficial in the sense that there is no need for deep processing in order to determine the value of the stimulus. Emotions are more closely tied to the self and the meaning of social situations. Emotion can be related to a reflective model of aesthetic involvement whereby a person interprets the work in terms of relevant aesthetic knowledge and personal life experiences. This search for underlying layers of meaning leads to deeper aesthetic engagement and emotional elaboration. The main point here is that processes related to the experience of feelings and emotions run concurrently. Feelings reflect more global responses to events involving characters and plots. Emotions are more firmly grounded in the search for meaning in depicted situations and implicate the lives of audiences who watch the programs.
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 | 0.003 | 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 | 0.000 | 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) | 0.000 | 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