Comcast's cable customers tumble as cord-cutting picks up
Bibliographic record
Abstract
Comcast's video upswing could be sputtering out. The cable company added TV customers last year for the first time in a decade. But on Thursday it posted its biggest quarterly cable-customer loss since 2014. Comcast's video upswing could be sputtering out.The cable company added TV customers last year for the first time in a decade. But it posted its biggest quarterly cable-customer loss since 2014.Research firm MoffettNathanson predicts that industrywide cable subscriptions fell 3.4 percent in the third quarter. That would mean that people are ditching their TV subscriptions faster than ever before.Partly to blame in the July-September quarter were the hurricanes that struck Texas and Florida, damaging poles, wires and other infrastructure and interrupting service for millions.But Comcast and other cable companies also say competition from online sources of video is taking a toll.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.025 |
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; both teacher heads agree on what is shown here.
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".