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Record W4288720124 · doi:10.54103/2037-3597/18338

PROGETTARE PERCORSI “VERTICALI” SULL’ARGOMENTAZIONE, TRA MODELLI DESCRITTIVI E PROPOSTE DIDATTICHE

2022· article· it· W4288720124 on OpenAlexaff
Valentina Bianchi

Bibliographic record

VenueItaliano LinguaDue · 2022
Typearticle
Languageit
FieldComputer Science
TopicLinguistic Studies and Language Acquisition
Canadian institutionsQuest University Canada
Fundersnot available
KeywordsHumanitiesArgumentativeArgumentation theorySociologyPhilosophyEpistemology

Abstract

fetched live from OpenAlex

L’argomentazione è una pratica complessa e, allo stesso tempo, cruciale per il nostro agire (sociale) quotidiano: saper argomentare rientra, infatti, tra i principali obiettivi da raggiungere alla fine del percorso scolastico. A tal fine, diventa imprescindibile la realizzazione di un curricolo verticale che preveda un iter graduale di avvicinamento all’atto argomentativo (e ai suoi processi costitutivi) e che, dalla scuola primaria, in una prospettiva di continuità organica e sistematica, accompagni il discente fino all’esame finale del secondo ciclo. Considerando la dimensione testuale (e la pratica di interazione con la multiformità dei testi argomentativi) il filo conduttore dell’intero percorso, dopo aver illustrato i principi e i modelli teorici utili alla definizione della struttura argomentativa e dei dispositivi linguistici su cui si regge, con questo lavoro si prova ad avanzare una serie di proposte didattiche concrete da poter sviluppare anche in aula.
 
 Designing “vertical” paths on argumentation, between descriptive models and teaching proposals 
 Argumentation is a complex practice and, at the same time, crucial for our (social) daily interaction: being able to argue is one of the main objectives to reach at the end of the school career. To this end, it becomes essential to create a vertical curriculum that provides a gradual approach to the act of argumentation (and its constituent processes) and that, from elementary school, in a perspective of organic and systematic continuity, accompanies the learner until the final exam of the second cycle. Considering the textual dimension (and the practice of interaction with the multiformity of argumentative texts) as the guiding thread of the entire course, after illustrating the principles and theoretical models useful for the definition of the argumentative structure and the linguistic devices on which it is based, this paper attempts to suggest a series of concrete didactic proposals that can also be developed in the classroom.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.519
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0020.002
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 head0.020
GPT teacher head0.245
Teacher spread0.225 · 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 teacher head, not a consensus.

Study designSimulation or modeling
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
Published2022
Admission routes1
Has abstractyes

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