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Record W3201309841 · doi:10.32370/ia_2021_09_8

The Concept of Distributivity In Old High German and Middle High German Texts

2021· article· en· W3201309841 on OpenAlexvenueno aff
Galyna Iarmolovych

Bibliographic record

VenueIntellectual Archive · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics and language evolution
Canadian institutionsnot available
Fundersnot available
KeywordsGermanNumeral systemDistributive propertyDistributivityLinguisticsMiddle AgesEtymologyFocus (optics)ConsciousnessComputer scienceEpistemologyMathematicsHistoryPhilosophyArtificial intelligencePure mathematics

Abstract

fetched live from OpenAlex

Quantification and numbers, numerals and number words have been in the focus of research on different levels of linguistical studies. The mathematical thinking and understanding of primitive arithmetical manipulations have been covered from both the mathematical and psychological points of view. The concept of distribution developed from the ability to group objects and belongs to the second wave of the mathematical understanding of primitive people. Being one of the first concepts developed in the human consciousness it stayed un-nominalised until the development of the number consequence paradigm. The distributive constructs existing in the Modern German language are a result of development from the Proto Indo European through the Proto Germanic, Old High German, and Middle High German languages. However, the modern standard concept of distributivity is built on the preceding word – i.e., a number of colloquial variations keep being used in some German dialects.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.004
Science and technology studies0.0020.008
Scholarly communication0.0040.004
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.235
Teacher spread0.218 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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