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Record W2561111508 · doi:10.1075/sibil.51.04kla

When masculine as default supercedes L1 transfer

2016· book-chapter· en· W2561111508 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

VenueStudies in bilingualism · 2016
Typebook-chapter
Languageen
FieldSocial Sciences
TopicGender Studies in Language
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsGermanGrammatical genderLinguisticsValue (mathematics)PsychologyFirst languageRepresentation (politics)Second languagePolitical scienceComputer science

Abstract

fetched live from OpenAlex

Previous research has shown that L2 gender use strategies vary according to the bilingual’s L1, with native speakers of languages without grammatical gender (such as English) tending to use masculine as a default while native speakers of languages with a gender feature (such as Spanish) opt for transfer of the L1 gender value. In this study we examine L1 Spanish-L2 German bilinguals’ use of gender in the L2 through an analysis of errors in oral production value. The results showed that, contrary to what has previously been found for L1 speakers of languages with grammatical gender, these bilinguals tended to use masculine as a default strategy. We argue that the difference in L2 gender use strategy is due to the unique representation of the Spanish and German gender systems.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.730
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.097
GPT teacher head0.394
Teacher spread0.297 · 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