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Getting the Message

2021· book· en· W4232504149 on OpenAlexaboutno aff
L. Solymár

Bibliographic record

VenueOxford University Press eBooks · 2021
Typebook
Languageen
FieldComputer Science
TopicHistory of Computing Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsTelegraphyTelecommunicationsTelephonyEngineeringBroadcasting (networking)MonopolyMedia studiesSociologyComputer scienceComputer security

Abstract

fetched live from OpenAlex

Laszlo Solymar’s book is quite unique in the sense that it is the only one that covers all the major developments in the history of telecommunications for the past 4,000 years, like fire signals, the mechanical telegraph, the electrical telegraph, telephony, optical fibres, fax, satellites, mobile phones, the Internet, the digital revolution, the role of computers, and also some long-forgotten technologies like news broadcasting by a devoted telephone network. It tells the technical aspects of the story but also how it affects people and society; e.g.it discusses the effect of the electric telegraph on war and diplomacy, how thanks to the telegraph Kitchener could preserve the Cairo-to-Cape Town red band for the British Empire, or more recent events like the effect of deregulation upon the monopoly of the American Telephone and Telegraph Company (AT&T). A number of anecdotes are told, e.g. how one murderer was caught by telegraphy when he arrived at Paddington Station and how another murderer was caught by wireless telegraphy when tried to escape by boat from Britain to Canada. The last chapter is concerned with the future: how the future was envisaged in the past and how we imagine the future of telecommunications now.

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)0.001
metaresearch head score (Gemma)0.004
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.232
Threshold uncertainty score0.775

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0080.010
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.2320.192

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 head0.019
GPT teacher head0.190
Teacher spread0.171 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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Same venueOxford University Press eBooksSame topicHistory of Computing TechnologiesFrench-language works237,207