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Record W2588910790 · doi:10.30827/digibug.53942

Nineteenth-Century English Fiction as a Source for Teaching Discourse Presentation Strategies to Spanish EFL Students: A Corpus-Based Approach to Direct Speech Reporting Verbs

2016· article· en· W2588910790 on OpenAlex
Pablo Ruano San Segundo

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

VenuePorta Linguarum Revista Interuniversitaria de Didáctica de las Lenguas Extranjeras · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicSpanish Linguistics and Language Studies
Canadian institutionsVictoria Park
Fundersnot available
KeywordsPresentation (obstetrics)LinguisticsIndirect speechCorpus linguisticsDirect speechPsychologyComputer scienceHistoryPhilosophyMedicine

Abstract

fetched live from OpenAlex

Direct speech has traditionally lacked the attention devoted to indirect speech
\nin EFL teaching in the Spanish curriculum. The verbatim representation of the speech act
\nbeing reported seems as a taken-for-granted construction which does not need further analysis.
\nThanks to a corpus-based approach, though, it is possible to retrieve data that prove
\notherwise. Reporting verbs will be the element under analysis, since they make it possible
\nto demonstrate that the way in which discourse is projected can be highly interpretative. The
\nanalysis will consist of a corpus-based study of more than eighty English Victorian novels (c.
\n16.8 million words). It will be carried out with WordSmith Tools (Scott, 2013), which allows
\nthe retrieval of more than 30,000 verbs.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.709
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.296
Teacher spread0.279 · 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