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Record W2249581867

Place et rôle des langues et cultures de l'Antiquité dans l'enseignement du français à l'école primaire de 1882 à nos jours en France

2015· dissertation· fr· W2249581867 on OpenAlexaff
Ida Iwaszko

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2015
Typedissertation
Languagefr
FieldArts and Humanities
TopicHistorical Linguistics and Language Studies
Canadian institutionsCanadian Heritage
Fundersnot available
KeywordsHumanitiesFrenchPhilosophyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

French language was and still remains the priority of French primary school. Despite this will, reality is a bit different: learning French remains complicated at school, there are big gaps between pupils. According to the results from PISA's survey (2012), our system of education is « very good » at creating even more inequalities between pupils. How can such difference be explained? Moreover, why is French so hard to teach and to learn? In order to answer these questions, a diachronic approach was salutary in many respects. At first, it is important to describe and to understand how our school was built. In addition, the place of Classics – Latin and Ancient Greek – was once great in our system, and their nearly disappearance had serious consequences on French learning. Indeed, the history of the language and the discipline shows us that French could not have been taught without classics for a long time. In our analysis, we question these links and we consider introducing classics in French learning at primary school. Classics reveal themselves to be very precious tools in order to create postures among pupils – reflexive, metalinguistic and epistemic – which allow them to succeed. They help all pupils to acquire strategies, which enable them to learn a rich language, therefore to develop a rich mind. Moreover, antic culture is at the basis of all fields of knowledge, it is a link between all disciplines and it makes them meaningful.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.856
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.242
Teacher spread0.233 · 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 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
Published2015
Admission routes1
Has abstractyes

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