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Record W4285385171 · doi:10.1017/9781108864183.009

<i>Uh,</i> <i> What Should We Count?</i>

2022· book-chapter· en· W4285385171 on OpenAlexaboutno aff
Tim Gadanidis, Derek Denis

Bibliographic record

VenueCambridge University Press eBooks · 2022
Typebook-chapter
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsnot available
Fundersnot available
KeywordsUtterancePosition (finance)DemographyStage (stratigraphy)Demographic economicsHistoryGeographyLinguisticsSociologyEconomicsPhilosophy

Abstract

fetched live from OpenAlex

One of the most dramatic discourse–pragmatic changes in twentieth–century English has progressed under the radar of laypeople and (until recently) linguists: the rise of um as the predominant variant of the “filled pause” variable (UHM) at the expense of uh. We investigate UHM at an early stage of change to determine what triggered its rise. We employ the variationist method to examine UHM in the Farm Work and Farm Life Since 1890 corpus of oral histories (recorded in 1984 with elderly farmers in Ontario, Canada). Nearly 5,000 tokens were extracted and coded for speaker birth year, gender, region, and utterance position. The overall frequency of um among the farmers is 11 percent. We find no significant effect of gender (12 percent for women, 10 percent for men). In one region, there is an effect of birth year. Lastly, we find no effect of utterance position. Looking at the frequency of each variant per 1,000 words, however, we see that, while the rate of um remains relatively stable, the rate of uh increases rapidly with year of birth, particularly with non–initial tokens produced by female speakers. Our results indicate that this data covers the first stage of this change.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.836
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.052
GPT teacher head0.255
Teacher spread0.202 · 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
GenreOther

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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

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