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Record W1559127666

Sticking one’s nose in the data : Evaluation in phraseological sequences with nose

2007· article· en· W1559127666 on OpenAlexaboutno aff
Magnus Levin, Hans Lindquist

Bibliographic record

VenueMalmö University Publications (Malmö University) · 2007
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsnot available
Fundersnot available
KeywordsNoseLinguisticsGermanic languagesComputer scienceNatural language processingArtificial intelligenceGeologyPhilosophyPaleontology
DOInot available

Abstract

fetched live from OpenAlex

With the realization that introspection and the use of dictionaries constitute a
\nprecarious foundation for studies of metaphor and metonymy, corpora have in
\nrecent years been used increasingly in the endeavour to explore the authentic use
\nof figurative language (see, e.g. Deignan 2005; Stefanowitsch and Gries 2006).
\nSimilarly, investigations of phraseology (e.g. Moon 1998) have come to rely
\nheavily on modern large-scale corpora, while analyses of evaluative lexis in the
\ntradition of John Sinclair (e.g. Sinclair passim; Hunston and Thompson 1999;
\nStubbs 2001) have a theoretical commitment to the corpus as an indispensable
\ntool. The present paper brings together these theoretical strands.
\nIt is commonplace in cognitive linguistics that human cognition is embodied
\n(cf. Lakoff and Johnson 1980; Langacker 1987, 1991; Kövecses and Szabó
\n1996; Gibbs and Wilson 2002; Gibbs et al. 2004). Therefore it is no surprise that
\nmany phraseological sequences are built up around words related to the body,
\nand in this corpus-based case study we have chosen to focus on the evaluative
\nfunctions of metonymic and metaphorical sequences containing the noun nose.
\nIn comparison with other body parts, such as the hand and the mouth, the nose is
\nfairly restricted in its use. Whereas in some cultures, like Maori and Inuit, the
\nnose has an additional social importance as it is used for greeting, in western
\nsocieties the nose seems to have predominantly negative or humorous connotations
\n(cf. Gogol’s The Nose). One can only speculate about the reasons for this:
\nperhaps it is the predominance of bad smells, or the association with snoring and
\nthe excretion of mucus. Some sequences containing nose also imply that the
\nagent is behaving like an animal. As an example of the latter type of connotations,
\nconsider (1) to (3) with the metonymic sequence stick one’s nose somewhere.
\nThis sequence is most frequently negative, as in (1), sometimes slightly
\nironic, as in (2), and occasionally positive, as in (3) (see further section 4.1.1). (1) The Steinbrenner we remember was always sticking his nose in where
\nit’s not wanted. (NYT 1996)
\n(2) As soon as it’s nice enough to stick your nose outside, this place is
\npacked (…) (Ind 2000)
\n(3) Stick your nose in it. Grind it out. You can’t be turning the other cheek
\nall the time. (NYT 1990)
\nIn contrast to most studies of evaluative language we will consider both
\ninstances where speakers express their opinions about other people’s activities
\nand cases where the disapproval is on the part of the agent in the clause without
\nthe speakers conveying their opinions of this.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.682
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.105
GPT teacher head0.310
Teacher spread0.205 · 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 designObservational
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

Citations6
Published2007
Admission routes1
Has abstractyes

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