MétaCan
Menu
Back to cohort
Record W4403673086 · doi:10.17118/11143/22001

Lingüística de legos en la prensa Argentina : el caso Francisco Ortiga Anckermann

2024· article· es· W4403673086 on OpenAlexvenueno aff
Eugenia Ortiz Gambetta

Bibliographic record

VenueCircula · 2024
Typearticle
Languagees
FieldArts and Humanities
TopicSpanish Linguistics and Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Resumen : Este artículo se propone analizar las columnas de la lengua de Francisco Ortiga Anckermann, al que considero uno de los periodistas más representativos de la lingüística de legos en la prensa argentina de comienzos del siglo XX. Bajo el seudónimo de “Pescatore di Perle”, escribió durante décadas diversas columnas de la lengua en las que señalaba los errores gramaticales, semánticos y ortotipográficos de recortes de la prensa y otros textos, a partir de material que le enviaban sus lectores. Como referente semi-autorizado de la lengua, Ortiga Anckermann se posicionó como un censor que apelaba al sentido común de la lengua, y criticaba sus usos incorrectos, mediante el humor. Tanto en las columnas como en su libro Antología del disparate (1934), Ortiga hizo una propuesta interesante: por un lado, detectó fallos pero sobre todo, insistió en los abusos de estilo, especialmente la hipercorrección, aquello que Lugones llamaría cursiparla; por el otro, incorporó el lunfardo, el cocoliche y ciertos giros orales como parte de un gesto ambigüo en cuanto al empleo del argot y su permeabilidad en la lengua literaria.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.151
Threshold uncertainty score0.300

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.005
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.014
GPT teacher head0.275
Teacher spread0.261 · 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 designQualitative
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueCirculaSame topicSpanish Linguistics and Language StudiesFrench-language works237,207