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 examining how framing influences an audience’s appreciation of products, practices, and people, including the framer, we take the perspective of the audience that evaluates the framing. We examine the effects of framing on evaluations when audiences are exposed to a multiplicity of frames, both by the same actor as the result of recurrent communications over time and by multiple actors who vie for attention. Using 36,012 research reports by securities analysts, covering the biotechnology and pharmaceutical industry between 1989 and 2012, we tested the relationships between analysts’ framing repertoires and professional investors’ evaluations of analysts as measured in the publication of Institutional Investor’s short list of the best analysts of the year. We found that investors appreciate analysts with framing repertoires that resonate with their needs, that are internally coherent over time, and that offer a moderate amount of novelty in comparison to others’ framings. We also found that framing is particularly important for analysts without existing high status, that is, who have never before been recognized as stars or who cannot benefit from association with a prestigious employer.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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