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Record W4407218875 · doi:10.3986/sls.2.1.01

On Derivational Productivity in Slovene with Notes on Lexical Frequency and Awareness of the Norm

2025· article· en· W4407218875 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

VenueSlovene Linguistic Studies · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics and language evolution
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLinguisticsNorm (philosophy)ProductivityMathematicsPsychologyPhilosophyEconomicsEpistemologyMacroeconomics

Abstract

fetched live from OpenAlex

The major aim of the study reported here was to discover a way of measuring the productivity of derivative patterns or processes, a task which appears never to have been accomplished for any language before. As specific material for the study, two contrasting deadjectival verbal derivative patterns were chosen: the 'inchoative' -eti and the 'factitive' -iti, as occurring in, e.g., rjav 'brown', rjaveti 'to become brown', rjaviti 'to make (someone or something) brown.' The method involved psycholinguistic tests, administered in Ljubljana in 1993—94. The subjects for the tests in 1993 were 186 secondary and 180 post-secondary students. For the 1994 follow-up study the tests were limited to three groups of university respondents, totalling 116 in all. Cues comprised four questions: (1) Ali se po vašem beseda nahaja v knjižni slovenščini? (2) Ali vi to besedo kdaj uporabljate? (3) Ali je ta beseda po vašem možna in razumljiva? (4) Kako pogosto sami uporabljate to besedo? Subjects selected responses on five-point Likert scales; the data were analyzed statistically. As far as productivity is concerned, there are three conclusions. First, it is clear that, at least for these derivative patterns, productivity is a "cline,'' but in two quite distinct meanings of the term. First and most obviously, one process may be synchronically more productive than another. Second, what may be called the productive strength of any one process also varies. To take just two examples from the mean responses to question (3), we see that the cue godneti was assessed, on average, as extremely "possible and understandable," while at the other end of the scale the cue plašeti was assessed, on average, as well nigh impossible and incomprehensible; the remaining cues are strung out along the cline in between the two.

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)0.005
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: Empirical
Teacher disagreement score0.438
Threshold uncertainty score0.586

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
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)0.0000.000

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 head0.033
GPT teacher head0.285
Teacher spread0.252 · 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