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Record W2792060362 · doi:10.1075/lv.15017.mas

Obligatorily null pronouns in the instructional register and beyond

2017· article· en· W2792060362 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

VenueLinguistic Variation · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNull (SQL)LinguisticsFocus (optics)Subject pronounComputer scienceRegister (sociolinguistics)Reflexive pronounNatural language processingPsychologyMathematicsPhysicsPhilosophy

Abstract

fetched live from OpenAlex

Abstract English is not canonically considered a pro-drop language. Despite this, it does allow null pronouns, although less freely than traditional pro-drop languages like Italian and Japanese. The focus of this paper is the instructional register (characteristic of recipes) where we claim that object pronouns are obligatorily null in English: “Take 3 eggs. Break _ into a bowl.”. We present an analysis of Instructional Register Null Objects that also accounts for obligatorily null pronouns in certain radical pro-drop languages like Niuean. In this language, most pronouns are optionally null, however 3rd person inanimate pronouns are obligatorily null. We argue that the obligatorily null nature of such pronouns (whether register-specific like in English, or general as in Niuean) is a result of their lack of φ-features, which leaves them with only the option of being realized through Neeleman & Szendrői’s (2007) general Zero Spell-out Rule.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.603
Threshold uncertainty score0.856

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.029
GPT teacher head0.252
Teacher spread0.222 · 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