The impact of consumer multi-homing on advertising markets and media competition
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 develop a model of advertising markets in an environment where consumers may switch (or "multi-home") across publishers. Consumer switching generates inefficiency in the process of matching advertisers to consumers, because advertisers may not reach some consumers and may impress others too many times. We find that when advertisers are heterogeneous in their valuations for reaching consumers, the switchinginduced inefficiency leads lower-value advertisers to advertise on a limited set of publishers, reducing the effective demand for advertising and thus depressing prices. As the share of switching consumers expands (e.g., when consumers adopt the Internet for news or increase their use of aggregators), ad prices fall.We demonstrate that increased switching creates an incentive for publishers to invest in quality as well as extend the number of unique users, because larger publishers are favored by advertisers seeking broader "reach" (more unique users) while avoiding inefficient duplication.
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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 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.006 |
| 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