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 construct a modified Hotelling‐type model of two media providers, each of whom can issue fake and/or real news and each of whom can invest in the debunking of their rival’s fake news. The model assumes that consumers have an innate preference for one provider or the other and value real news. However, that valuation varies according to their bias favouring one provider or the other. We demonstrate a unique subgame perfect Nash equilibrium in which only one firm issues fake news and we show, in this setting, that increased polarisation of consumers (represented by a wider distribution) increases the prevalence of both fake news and debunking expenditures and is welfare‐reducing. We also show, inter alia , that a stronger preference by consumers for their preferred provider lowers both fake news and debunking. Finally, we compare monopoly and duopoly market structures in terms of ‘fake news’ provision and show that a public news provider can be welfare‐improving.
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 | 0.000 | 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) | 0.002 | 0.002 |
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