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Record W2016224432 · doi:10.1353/lan.2007.0109

<b>Language matters:</b> A guide to everyday questions about language. By Donna Jo Napoli. Oxford: Oxford University Press, 2003. Pp. x, 198. ISBN 0195160487. $19.95.

2007· article· en· W2016224432 on OpenAlexaboutno aff
Gregory Ward

Bibliographic record

VenueLanguage · 2007
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)LinguisticsLanguage acquisitionComprehension approachOn LanguageEveryday lifeScope (computer science)PsychologyComputer scienceCognitive scienceLanguage educationEpistemologyHistoryPhilosophy

Abstract

fetched live from OpenAlex

Reviewed by: Language matters: A guide to everyday questions about language by Donna Jo Napoli Gregory Ward Language matters: A guide to everyday questions about language. By Donna Jo Napoli. Oxford: Oxford University Press, 2003. Pp. x, 198. ISBN 0195160487. $19.95. In a nutshell, this is a great little book—small in size (measuring 5″ × 7″) and short in length (198 pp.), but grand in scope. Billed as ‘A guide to everyday questions about language’, this book provides answers to what are arguably the dozen most common questions that professional [End Page 654] linguists are asked by nonspecialists (including students and highly educated nonlinguists as well as nonacademics). According to the author, each of the answers to these twelve questions is designed to address one or more misconceptions associated with that question, and each question constitutes a separate chapter, ranging in length from eleven to twenty-two pages. Part 1 (Chs. 1–6) deals with language as a human ability and Part 2 (Chs. 7–12) deals with language in its broader social context. Ch. 1 (‘How do we acquire language?’) provides a very general overview of the basic features of language acquisition, with an emphasis on its biological basis: ‘For the past half century, linguists have hypothesized that there is a language mechanism in the brain, an actual physical mechanism, that is responsible for all aspects of language, including learning, processing, and production’ (5). Of course the validity of this claim depends in part on what is meant by ‘all aspects of language’; presumably some of the more context-sensitive aspects of language (i.e. those governing conversational and social interaction or particularized conversational implicature) are not entirely governed by the same mechanism that controls syntax and phonology. That notwithstanding, the chapter gives the reader a very accessible introduction to one of the major findings of the discipline that also serves as a source of rampant misconceptions about language, namely: ‘We are hard-wired to process and produce natural human language’ (15). Ch. 2 (‘From one language to the next: Why is it hard to learn a second language? Why is translation so difficult?’) introduces the reader to some of the issues and problems associated with translation. N uses a Dutch nursery rhyme as an illustration. For example, should proper names (and diminutives) be imported directly into the target language or should social/stylistic equivalents be found? Should the preservation of rhyme and meter be at the expense of the preservation of lexical meaning? Should cultural equivalence be preserved? N uses the example of turkey being mentioned in the context of a festive dinner table, connoting perhaps an American thanksgiving dinner. In translating ‘turkey’ into other languages, should a different, culturally appropriate, food item be used to evoke the same imagery? Or should the translation be as ‘literal’ as possible (whatever that means)? The result of this line of questioning is the inevitable conclusion that ‘translation is not a mechanical act; it doesn’t proceed by any sort of simple algorithm. Rather, translation is a creative act’ (33). Ch. 3 (‘Does language equal thought?’) addresses the interrelated questions ‘Do we think in language?’ and ‘Could we think without a language?’. No introductory discussion of language and thought would be complete, of course, without reference to that old linguistic chestnut regarding the number of words for snow in Inuit, and N does not disappoint (although the Sapir-Whorf hypothesis is never mentioned by name). As N puts it, ‘There are many things we are surrounded by in great quantity that we do not have lots of words for’ (42). As a further illustration of the independence of language and thought, N uses the nonexistence of resultative secondary predicates (e.g. John beat the eggs stiff) in Romance languages to illustrate that the difference between English and Romance in this regard is not conceptual but grammatical. While a fine example of the general point, the use of linguistic jargon here might be a little off-putting to some readers. Ch. 4 (‘Are sign languages real languages?’) covers some basic linguistic facts and figures (the arbitrariness of the sign, the creative nature of language), while embedding them in a novel context...

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.008
GPT teacher head0.283
Teacher spread0.274 · 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.

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

Citations1
Published2007
Admission routes1
Has abstractyes

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