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Record W2102219666

On Language Wars

2015· article· en· W2102219666 on OpenAlexaboutno aff
Michael Moore

Bibliographic record

VenueETC.: A Review of General Semantics · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics, Language Diversity, and Identity
Canadian institutionsnot available
Fundersnot available
KeywordsPower (physics)LinguisticsIndependence (probability theory)AdversaryHistoryLawPolitical scienceSociologyPhilosophyMathematics
DOInot available

Abstract

fetched live from OpenAlex

A is a dialect with an army and Navy, attributed to Yiddish linguist Max WeinreichIn Belgium, Canada, Spain, Sri Lanka, and Turkey, has been il most important factor in ethnic conflict wrote Safran (2010, p. 58) concerning violent clashes in these multilingual countries; he could have added, inter alia, fierce Urdu-Bangla battles that followed India's independence in 1947. But in Language Wars I speak of no one fires bullets, cannon balls, or other material missiles at enemy-the combatants use as ammunition words about which they fight.1 On one side of barricades we find defenders of our language,2 adherents to linguistic purism and prescriptivism who tend to label linguistic changes as corruption or bastardization. Opposed to them stand champions of linguistic descriptivism; they concur with Horace: will change if it be will of custom, in power of whose judgment is law and standard of language (aka Norma Loquendi, in Liberman, 2004).In following, I shall bring a sample of missives launched by brave soldiers of each camp against their enemies. Instead of listing thoughtful, well established arguments in favor of one position or other, I have selected a few emotionally laden ones. By focusing on affective, rather than cognitive components of their sources' attitudes, I hope to enrich our understanding of combatants and to provide us with an insight into their motivation.First, prescriptivists.3In 1797, English journalist William Cobbett attacked Noah Webster for grammatical inaccuracy and called him illiterate booby, inflated self-sufficient pedant, very great hypocrite, and something of a traitor (Liberman, 2005).George Orwell (2006) felt that the English is in a bad way It becomes ugly and inaccurate because our thoughts are foolish, but slovenliness of our makes it easier for us to have foolish thoughts. He went on, illustrating his complaints with such metaphors as mental vices and the decay of language.Urbanczyk, a Polish communist linguist (in Janicki, 2006) wrote about ... linguistic skill and correctness without which it is difficult to think logically and creatively and impossible to convey thoughts to others.While previous description of corruptors of implies that they are illogical and incoherent, others have impugned their moral character, as well: ... because purification implies getting rid of stain and thus evil, purification movements imply at some level that impure elements belong to impure persons (Shapiro, 1989, p. 156).The Conservative MP Norman Tebbit found a similar slippery slope: If you allow standards to slip to stage where good English is no better than bad English, people turn up filthy at school all these tend to cause people to have no standards at all, and once you lose standards there's no imperative to stay out of crime (Nunberg, 2011).Acocella (2012) accused descriptivists of self-righteousness, while Bryson (1987, p. 177) sounded off on misuse of apostrophe: the mistake is inexcusable, and those who make it are linguistic Neanderthals.Vitriolic appears in descriptivist camp, as well. latter often refer to prescristivists as peevers, police, and grammar Nazis.Though John Ruskin wrote about architecture when he expressed following sentiment, his words equally apply to purists of other disciplines, including linguistics: The world is full of vulgar Purists, who bring discredit on all selection by silliness of their choice; and this more, because becoming a Purist is commonly indicative of some slight degree of weakness, readiness to be offended, or narrowness of understanding of ends of things (Ruskin, 1853).Liberman's (2008) appellation concerns some prescriptivists' lack of knowledge: . …

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.906

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.040
GPT teacher head0.278
Teacher spread0.238 · 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 teacher head, 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
Published2015
Admission routes1
Has abstractyes

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