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Record W294759000

Classical versus Vulgate/popular English. (On-Going Topics)

2002· article· en· W294759000 on OpenAlexaboutno aff
Melvin J. Hoffman

Bibliographic record

VenueAcademic exchange quarterly · 2002
Typearticle
Languageen
FieldArts and Humanities
TopicLexicography and Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsStress (linguistics)NewspaperVocabularyEntertainmentMedia studiesSociologyAdvertisingLinguisticsPolitical scienceLawBusiness
DOInot available

Abstract

fetched live from OpenAlex

Abstract This article explores technological change affecting international English. Before broadcast media, both educated and non-educated people relied on print news and entertainment. After that, popular media, mostly U.S. and U.K. provided common international English vocabulary of brand names, products, and personalities. The information age also brought new international English vocabulary, but cost and educational requirements limits availability to advantaged speakers of English whether native, second or foreign language. Consequently, two international English vocabularies exist. One is popular and widespread; the other concerns finance, technology and the academy. ********** Industrial developments in 18th and 19th century Anglophone nations accompanied trade-union and public-education growth, and newspaper preeminence before broadcast media. Class-conscious Britain marked social status by accent, grammar and vocabulary, but people with enough money could hire tutors like Eliza Doolittle. (G.B. Shaw, 1999-2000) Others--in domestic service, sales, and other contact with genteel speakers--could upgrade if they could model speech. Standard U.S. speech reflected less overt class-marking. Lawyers, doctors, diplomats, financiers, and others used vocabulary, opaque to laypersons, even after higher education dropped Latin. However, professions demanded less preparation as fewer began work in their late twenties or early thirties. Literacy, widespread in what became Anglophone G-7 nations, did not simply serve employment. Everyone obtained news through print; the illiterate had notices and articles read to them. Novels, short stories, and serialized works entertained both less and more educated. The Rise of Technology The 20th century brought change though film, record players, and radio. Videos did not exist; commercial radio began in 1926; fewer stations existed, and portables were not very portable. (Broadcasting, 1999-2000) The 1950s saw mass-produced affordable American televisions. (Broadcasting ... Television, 1999-2000) Also, MIT's Lincoln Laboratory's first computer network, Semi-Automatic Ground Environment linked missile sites. (Telecommunications ... SAGE, 1999-2000) The first time-sharing computer operating system, also MIT designed, began in 1961. In 1969, the Advanced Research Projects Agency's first network, ARPANET preceded the Internet, linking heterogeneous computers on military installations and tertiary institutions. (Telecommunications ... Advances in Telephony, 1999-2000) Throughout history, income disparities have created various inequities like unequal access to information. In the present, computers--crucial to international e-commerce and to lucerative professions--are costly. E-globalization has denied many English speakers international English vocabularies, limited to higher education and specialized work environments. Canada, the U.K. and the U.S., G-7 nations, affect world economic superstructure beyond their speakers' numbers. For example, the 1944 Bretton Woods conference begat the World Bank (2000) and International Monetary Fund (2000 [I.M.F.]), both later attached to the U.N. The former's board of governors is elected from every member nation. However, five of 24 directorships are permanent for the most financially supportive nations like the U.S. and the U.K. The I.M.F.'s 24 member board of directors operates similarly. Washington D.C. hosts both, and governors meet and directors conduct business twice or thrice weekly. Banking, business, and investment English is spoken, the international financial English of Anglophone Canada, the U.K. and the U.S. Similarly, delegates to the U.N.'s General Assembly work and reside in English-speaking New York City. The internet-served stock exchange in the city harboring the U.N., descends--ironically--from the military network ARPANET mentioned earlier. …

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)0.007
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.248

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0740.012

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 head0.062
GPT teacher head0.257
Teacher spread0.196 · 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
GenreEmpirical

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
Published2002
Admission routes1
Has abstractyes

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Same venueAcademic exchange quarterlySame topicLexicography and Language StudiesFrench-language works237,207