THE DEVELOPMENT TRENDS OF E–COMMERCE SERVICES IN THE UNITED STATES
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
The article deals with the latest trends in US trade in electronic services, in particular audiovisual services, computer services and data processing services, telecommunication services. Since 2007 trade of audiovisual services has been the most significant in theUSe-services export. The largest consumers of these services are the European Union, Asia and the Pacific region (the main consumers areChinaandIndia) and Central and South America (BrazilandArgentina). Among the countries, the main importers of American audiovisual services are theUK,CanadaandGermany. The main share of audiovisual services is occupied by film distribution and streaming media. In theUSAaudiovisual services are imported by theUK,Brazil,Mexico,CanadaandArgentina. For several years there is a deficit in the trade turnover of computer services in theUnited States. The main importers of these services from theUnited Statesare theUnited Kingdom.Canada,Switzerland,India,Germany. TheUSA, in turn, uses computer services fromIndia(47%),Canada,Ireland, theUKandGermany. The American telecommunications market is about a quarter of the world's, so theUSAis the largest national market for this type of service. The importing countries of theUStelecommunications services are theUnited Kingdom,Mexico,India,Canadaand theNetherlands, and the main export consumers areBrazil,Argentina, theUnited Kingdom,VenezuelaandCanada.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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