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 adapt Erving Goffman’s (1974) frame analysis to discover how frames shape individuals’ decisions in a poker-based experiment. The frames that surfaced in our subjects’ verbalizations suggest the ways in which they form very different impressions of “what is going on” in an identical situation. Our findings revealed that people’s frames drive the information they attend to in a situation, the interpretation they put on that information, and the way they synthesize the information to make a decision. The thematic frames that emerged differed dramatically across groups of individuals; they also were cohesive, multifaceted, and relatively few in number. As a result they were predictive: one could foretell a person’s behavior across multiple situations given the consistency in the frame adopted. In most cases, frames also revealed a significant mismatch with the requirements of the situation. Management scholars and practitioners would be wise to be more alert to frames which can do as much to derail effective decision-making as to facilitate it.
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 | 0.001 |
| 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