A Curious Tale of Economics and Common Carriage (Net Neutrality) at the FCC: A Reply to Faulhaber, Singer, and Urschel
Bibliographic record
Abstract
This reply to “The Curious Absence of Economic Analysis at the Federal Communications Commission” by Faulhaber, Singer, and Urschel makes three claims. First, we document the paper’s undisclosed origins as a white paper commissioned by an advocacy group with deep ties to the telecommunications industry. Second, we describe two of the authors’ active participation, on behalf of clients, in a range of contested issues before the FCC in recent years. Finally, our review of FCC workshops, roundtables, seminars, dockets, and rulings—including during its landmark 2015 Open Internet Order and several blockbuster mergers and acquisitions—provides detailed evidence to refute the paper’s core “curious absence” charge. The stakes could not be higher, we conclude, as the new FCC chair, Ajit Pai, has repeatedly referenced the paper to justify his rollback of FCC regulations—including, crucially, the common carriage/net neutrality rules so vigorously opposed by the paper’s funders.
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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 | 0.033 | 0.121 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.048 |
| Scholarly communication | 0.020 | 0.021 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.046 | 0.059 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".