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Record W4365511433 · doi:10.1017/s0958344023000071

Beyond replication: An exact replication study of Łodzikowski (2021)

2023· article· en· W4365511433 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueReCALL · 2023
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsReplication (statistics)Computer scienceTranscription (linguistics)Protocol (science)LinguisticsMathematicsStatistics

Abstract

fetched live from OpenAlex

Abstract Replication studies have become an emerging line of research in recent decades, including in computer-assisted language learning (CALL). Exact replication, which closely follows a study’s protocol, is rare as it is hard to recreate results without establishing a highly controlled environment. However, using data available online, we were able to conduct an exact replication of Łodzikowski’s (2021) study, which reported on the use of an allophonic transcription tool by 55 Polish learners of English. Allophonic features are used by native speakers to produce acoustic variants of the same phoneme. The original study offered learners an allophonic transcription tool, examined how they used it and considered its association with phonological awareness. This study extended the original research by addressing the limitations of its regression and transcription analyses. Our findings allowed us to offer several suggestions on (1) how an allophonic transcription tool can be better designed to help learners, (2) how CALL researchers can acquire more data for more useful research and (3) why more replication studies are needed in CALL.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.838
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.087
GPT teacher head0.430
Teacher spread0.343 · 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