Bibliographic record
Abstract
Since the last decade of the twentieth century, internet access has become a sine qua non for businesses. IT as well as online commerce have been growing fast over the past decades, and many other sectors also depend more and more on internet access; even industrial services such as design and warehousing, to name but two examples, rely on and benefit from cooperation at a distance. The global boost in teleworking and particularly teleconferencing following the Covid-19 pandemic has shown how important reliable connections are. Governments have over the past decade invested in improving their connections to the worldwide internet. Yet it is not clear whether economic clustering in fact is attracted to well-connected locations. We therefore test empirically whether the level of connectedness to the global IT infrastructure has a correlation with subsequent economic growth in sectors that use such infrastructure, or even depend on it. We do this using a panel of US cities, in which we zoom in on a few sectors that can use the infrastructure and compare them against the background of other sectors in the same cities. As a measure for the quality of local connections, we employ a unique method: we use the latency (ping times), a network metric usually spurned in favour of the more common bandwidth.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".