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Record W3198509966 · doi:10.5380/rvx.v16i5.81217

Interview with Dr. Mary Grantham O’Brien: Looking at comprehensibility as a dynamic construct

2021· article· en· W3198509966 on OpenAlexaffabout
Cesar Teló, Mary Grantham O’Brien

Bibliographic record

VenueRevista X · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsConstruct (python library)Dimension (graph theory)PsychologyPsychoanalysisComputer scienceMathematicsProgramming language

Abstract

fetched live from OpenAlex

In 1995, Munro and Derwing changed the way second language (L2) speech is understood and researched. From that point on, applied linguists have adopted intelligibility (actual comprehension), comprehensibility (ease of understanding), and accentedness (degree of foreign accent), as global dimensions of L2 speech. Since the publication of Munro and Derwing's seminal work, a host of studies have investigated L2 speech learning from psycholinguistic and sociolinguistic perspectives in perception, production, longitudinal, and classroom-based designs. However, after more than two decades of carrying out research on global dimensions of L2 speech, changes in L2 pronunciation research methods began to arise (LEVIS, 2020; MUNRO; DERWING, 2020), and some researchers now conceive comprehensibility as dynamic rather than static. This means that listeners' perceptions of how easy it is to understand a speaker may vary on the basis of several variables. Dr. O'Brien, at the University of Calgary, together with colleagues across North America, is conducting trailblazing research on the malleability of comprehensibility. Their findings bring forward a new understanding of L2 speech; one that extrapolates traditional views of L2 pronunciation and expands the horizons of the field. In addition to investigating global dimensions of L2 speech as dynamic constructs, Dr. O'Brien has extensively looked into two other areas: The perception and production of prosodic cues (such as word stress, sentence stress, and intonation) to meaning, and

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.981
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0020.000

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 head0.026
GPT teacher head0.327
Teacher spread0.301 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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