Bibliographic record
Abstract
Future drafts at votermedia.org/publications Our existing media, both private sector and public sector, have inadequate economic incentives for serving voter interests in our democracies and shareowner interests in our corporations. As a result, we suffer from corruption and inefficient policies. To remedy this, we can create a new hybrid media sector, where organizations compete for funds allocated by voters. This would provide the financial support for media to build their reputations for critiquing politicians, directors and their policies, while remaining loyal to voters ’ interests. With more trustworthy information and insight, we will be able to use our voting power more effectively. The blogosphere’s recent growth and energy provide an ideal engine for launching this proposal. We can create a website platform for blog (and other media) competitions, one for each voting community in the world. Supported initially by donations, this system should prove valuable enough to voters that they will finance media awards from their community budgets. Early adopters of this proposal are likely to be smaller democracies like student unions and municipalities, followed eventually by co-ops, credit unions, associations, labor unions, then corporations and regional and national governments. Tests of this system have begun in Vancouver Canada. This paper describes the economic rationale for the proposed reform, system designs tested so far, the results achieved, and strategies for the next stage of the voter funded media movement. It should make elected leaders (politicians, boards of directors) more accountable to voters and the public interest, thus helping to solve the daunting range of global problems that humanity now faces.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.857 | 0.764 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".