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Record W4252777155 · doi:10.1017/s0008413100001055

A Level Playing-Field: Perceptibility and Inflection in English Compounds

2009· article· en· W4252777155 on OpenAlexaff
Robert Kirchner, Elena Nicoladis

Bibliographic record

VenueThe Canadian Journal of Linguistics / La revue canadienne de linguistique · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLinguisticsInflectionAffixPsychologyPerceptionRoot (linguistics)DiminutiveMeaning (existential)Philosophy

Abstract

fetched live from OpenAlex

Abstract To explain why English compounds generally avoid internal inflectional suffixation (e.g., key-chain rather than keys-chain ), linguists have often invoked the Level Ordering Hypothesis, that is, that particular types of morphology, in this case inflectional suffixation, are derivationally ordered after compounding. However, a broad range of counter-examples and conceptual objections to Level Ordering have emerged. We propose an alternative account, based on the observation that certain English inflectional suffixes are more perceptible than others ( -ing > -s > -ed ), and that these suffixes are less crucial to lexical access and recovery of meaning than corresponding root-final segments. This proposal was tested in perception and production experiments. In the perception experiment, compounds with a nonsense word as modifier (e.g., dacks van, dacked van ) were auditorily presented to native English speakers, who were asked to spell what they heard. The participants omitted significantly more -ed than -s or -ing . In the production experiment, native English speakers read these compounds. The speakers dropped significantly more -ed than -s or -ing . Furthermore, they dropped more of these sounds when they were spelled as affixes than as part of the root (e.g., dacked van vs. dact van ). These results suggest that English speakers’ avoidance or inclusion of inflection in compounds is based not on Level Ordering but on perceptibility, as well as the status of the consonant as an affix. We further present a formal analysis capturing these factors in terms of Steriade’s Licensing-by-Cue proposal.

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)0.006
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.027
GPT teacher head0.244
Teacher spread0.216 · 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

Citations3
Published2009
Admission routes1
Has abstractyes

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Same venueThe Canadian Journal of Linguistics / La revue canadienne de linguistiqueSame topicSyntax, Semantics, Linguistic VariationFrench-language works237,207