An Economic Response to Unsolicited Communication
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
Abstract If communication involves some transactions cost to both sender and recipient, what policy ensures that correct messages -- those with positive social surplus - get sent? Filters block messages that harm recipients but benefit senders by more than transactions costs. Taxes can block positive value messages, and allow harmful messages through. In contrast, we propose an ``Attention Bond,'' allowing recipients to define a price that senders must risk to deliver the initial message.The underlying problem is first-contact information asymmetry with negative externalities. Uninformed senders waste recipient attention through message pollution. Requiring attention bonds creates an attention market, effectively applying the Coase Theorem to price this scarce resource. In this market, screening mechanisms shift the burden of message classification from recipients to senders, who know message content. Price signals can also facilitate decentralized two-sided matching. In certain limited cases, this leads to greater welfare than use of even ``perfect'' filters.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.009 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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