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Record W7067261880

Le competenze tra mercato e democrazia. Riflessioni critiche a partire da C. Laval e G. Biesta

2025· article· it· W7067261880 on OpenAlexaboutno aff

Bibliographic record

VenueBOA (University of Milano-Bicocca) · 2025
Typearticle
Languageit
FieldMedicine
TopicCutaneous lymphoproliferative disorders research
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

Il concetto di competenza ha attraversato un’evoluzione significativa, passando da una concezione tecnico-operativa, centrata sulla misurabilità della performance, a un approccio più ampio e contestualizzato, che integra conoscenze, abilità e atteggiamenti in relazione ai contesti di apprendimento e di vita. Questa trasformazione ha avuto un impatto rilevante sulle politiche educative internazionali, europee e nazionali, contribuendo alla diffusione di modelli basati sull’apprendimento permanente e sulle competenze trasversali, considerate essenziali per rispondere alle sfide della globalizzazione e alle trasformazioni del mercato del lavoro. Tuttavia, l’orientamento verso un’educazione per competenze rischia di ridursi a un dispositivo funzionale all’occupabilità, subordinato a logiche neoliberiste che privilegiano la flessibilità e l’adattabilità dell’individuo alle esigenze economiche. L’obiettivo del contributo è, dunque, analizzare le implicazioni di questa trasformazione attraverso le prospettive critiche di Christian Laval e Gert Biesta, mettendo in luce il pericolo di una deriva performativa che svuoti la formazione della sua portata emancipativa. Sottolineare la necessità di recuperare la dimensione etica, politica e trasformativa dell’educazione muove verso la promozione di un approccio che, invece di piegarsi a logiche di efficientismo e produttività, si configura come spazio di emancipazione, partecipazione democratica e giustizia sociale.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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: Commentary · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0040.013
Scholarly communication0.0110.005
Open science0.0010.004
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0130.003

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 head0.018
GPT teacher head0.272
Teacher spread0.255 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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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