MétaCan
Menu
Back to cohort
Record W2114324581 · doi:10.1017/s0272263106230055

PROCESSING INSTRUCTION: THEORY, RESEARCH, AND COMMENTARY

2006· article· en· W2114324581 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 Second Language Acquisition · 2006
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsConcordia University
Fundersnot available
KeywordsPossessiveLinguisticsMeaning (existential)PsychologySecond languageSecond-language acquisitionPhilosophy

Abstract

fetched live from OpenAlex

PROCESSING INSTRUCTION: THEORY, RESEARCH, AND COMMENTARY. Bill VanPatten (Ed.) . Mahwah, NJ: Erlbaum, 2004. Pp. 360. $79.95 cloth. I have often been struck by how highly fluent second language (L2) speakers of English can make errors in, say, possessive determiner gender agreement (e.g., Chinese, French, or Russian speakers saying “his” instead of “her”) without being disturbed at all by what they have said. To me, as a first language speaker of English, the error is extremely jarring and can disrupt understanding. For the L2 speaker, the error has much less impact. By contrast, an error in lexical reference (e.g., saying “boy's” instead of “girl's”) is generally experienced as jarring and potentially disruptive, even by L2 speakers. Why, then, do L2 speakers perceive errors in linking grammatical form to meaning so differently than errors in linking lexical units to meaning? Does this difference pose a challenge for L2 instruction and, if so, how should the challenge be met?

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.436
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0200.000

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 head0.046
GPT teacher head0.407
Teacher spread0.362 · 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