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Record W4417361372 · doi:10.60923/issn.2704-8217/22239

Fonti storiche che educano alla pluralità: i canti di tradizione orale

2025· article· pt· W4417361372 on OpenAlexaff
Maria Nastasio, P. Bosio, Tiziana Porteri

Bibliographic record

VenueDidattica della storia – Journal of Research and Didactics of History · 2025
Typearticle
Languagept
FieldArts and Humanities
TopicHistorical and Literary Analyses
Canadian institutionsHôtel-Dieu Grace Healthcare
Fundersnot available
KeywordsStudioClass (philosophy)Key (lock)

Abstract

fetched live from OpenAlex

Il presente contributo propone alcune attività scolastiche di educazione alla pluralità basate sull’utilizzo dei canti di tradizione orale nello studio della storia. L’articolo ne mette in luce l’utilizzo quali preziose fonti per la lettura dei fatti storici da diverse prospettive, con particolare attenzione al punto di vista delle classi subalterne, spesso escluso dalle narrazioni canoniche.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.014
Scholarly communication0.0110.005
Open science0.0010.008
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0140.002

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 head0.096
GPT teacher head0.344
Teacher spread0.248 · 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
Published2025
Admission routes1
Has abstractyes

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