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Record W4318070448 · doi:10.1075/slcs.229

Serbian Clitics

2023· book· en· W4318070448 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 language companion series · 2023
Typebook
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsDalhousie University
Fundersnot available
KeywordsSerbianLinguisticsSentenceMeaning (existential)CliticElement (criminal law)HistoryPhilosophyPsychologyEpistemologyLaw

Abstract

fetched live from OpenAlex

Clitics, those “funny little words” like English contracted future tense and pluperfect tense/conditional mood markers (’ll and ’d) or French pronominal objects (le ‘him’, la ‘her’, lui ‘to him/her’, etc.), have long been a source of fascination for linguists. Lacking an inherent stress that characterizes “well-behaved” words, clitics prosodically depend on a stressed sentence element, called their host, which makes them look and, in some contexts, behave like affixes (parts of words). Some clitics, Serbian second-position clitics being the case in point, also obey stringent linear ordering rules, different from those holding for fully-fledged sentence elements. This monograph offers a comprehensive formalized description of second-position clitics in standard Serbian from the viewpoint of the Meaning-Text theory, an approach relying on syntactic dependencies and oriented towards speech production, which sets it apart from most contemporary frameworks. It will be of interest for general linguists, Slavists, and advanced learners of Serbian.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.325
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.084
GPT teacher head0.322
Teacher spread0.238 · 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