<b>Research Note</b>—Quality Uncertainty and the Performance of Online Sponsored Search Markets: An Empirical Investigation
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
Online sponsored search advertising has emerged as the dominant online advertising format largely because of their pay-for-performance nature, wherein advertising expenditures are closely tied to outcomes. While the pay-for-performance format substantially reduces the wastage incurred by advertisers compared to traditional pay-per-exposure advertising formats, the reduction of such wastage also carries the risk of reducing the signaling properties of advertising. Lacking a separating equilibrium, low-quality firms in these markets may be able to mimic the advertising strategies of high-quality firms. This study examines this issue in the context of online sponsored search markets. Using data gathered from sponsored search auctions for keywords in a market without intervention by the intermediary, we find evidence of adverse selection for products/services characterized by high uncertainty. On the other hand, there is no evidence of adverse selection for similar products in a regulated sponsored search market, suggesting that intervention by the search intermediary can have a significant impact on market outcomes and consumer welfare.
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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 | 0.033 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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