Bibliographic record
Abstract
"The Enduring Lessons of the Breakup of AT&T: A Twenty-Five Year Retrospective."' Conference held at the University of Pennsylvania Law School on April 18-19, 2008. Did the Divestiture of AT&T achieve its purpose? It is helpful to turn to Canada, whose telecommunications industry and regulation were similar but which did not experience a divestiture. Since AT&T was split up in 1982-4, national telecom market concentration in the U.S. has bounced back to a national duopoly structure, with an HHI concentration index of 2,986, higher than for Canada's similar national duopoly with an HHI of 2,463. Local telecom wireline competition is greater in Canada, as are broadband and wireless penetrations. Real revenue for all of AT&T's successor companies grew only half as much as in Canada. AT&T successors' combined market capitalization rose only one third as much as did Bell Canada. U.S. telecom prices are more favorable to business, low-use consumers, and mobile users, but less favorable to high-use consumers, especially those making long distance calls. AT&T's research development sector was decimated while Canada has preserved some reduced in-house research. Employment in the U.S. declined slightly after 1997, whereas in Canada it rose over 20%. Taken together, this comparison does not indicate that the AT&T divestiture created advantages relative to Canada.
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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.012 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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 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".