MétaCan
Menu
← Back to cohort
Record W2990818426 · doi:10.4324/9781351115704-10

The economics of international telecommunications

2018· book-chapter· en· W2990818426 on OpenAlexaboutno aff
Alfred C. Sikes

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

Telecommunications used to consist chiefly of voice traffic, linking subscribers across town, or throughout a government or country, or occasionally internationally. Telecommunications in sum has become essential as a modern business tool. The financial services, transportation, insurance, retailing, travel and tourism, and a whole array of other political industries, depend on the availability of effective and efficient telecommunications. International trade have been an outgrowth of shared national perspectives, especially in understanding the value of information and information services. In much of Europe, for instance, government-owned post and telecommunications entities effectively monopolized communications products and services. In the United States and Canada, the telephone companies were vertically integrated into all stages of production, equipment, local and long-distance services. Developed countries&s; economies is highly desirable as a matter of domestic and international policy that steps toward more open and freer telecommunications markets continue to accelerate.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.017
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.004
Scholarly communication0.0060.004
Open science0.0000.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0170.004

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.

Opus teacher head0.017
GPT teacher head0.231
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same topicICT Impact and Policies→French-language works237,207→