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L'éducation, un aspect des relations culturelles Cameroun -Canada (1948-2008)

2013· dissertation· en· W22365788 on OpenAlexaboutno aff
Guillaume Bivina

Bibliographic record

VenueEating Behaviors · 2013
Typedissertation
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArtEthnologySociology

Abstract

fetched live from OpenAlex

En 2010, le Cameroun a fete le centenaire de l’education moderne et le cinquantenaire de son independance. Pour les generations adultes, le niveau scolaire a dangereusement baisse. Selon eux, les eleves etaient jadis plus consciencieux et plus performants. A ce titre, les etablissements scolaires BONNEAU, SACRE-COEUR, SAINT-COEUR, VOGT, STOLL, evoquent tout ce qu’il y a de serieux. Les personnalites de premier rangdu Cameroun a l’exemple du Chef de l’Etat actuel, y ont ete formees par des missionnaires canadiens. Voulant savoir ce qui faisait la particularite de cette education, nous avons emis l’hypothese generale qu’elle reposait sur une approche didactique particuliere. Cette hypothese nous a permis de consulter des archives pour examiner les aspects ethiques, socioprofessionnels, psychopedagogiques et technologiques des educateurs canadiens. Il en ressort que les valeurs ethiques et morales etaient au coeur de leur approche educative. Le profil des enseignants de ces etablissements etait moins important que les valeurs chretiennes qu’ils incarnaient. Aussi avons-nous propose que les educateurs camerounais actuels s’inspirent de ce modele pour ameliorer leur pratique. En somme, il nous est apparu hautement souhaitable que les professeurs d’histoire, s’appuyant sur l’approche ethique canadienne, presentent des valeurs authentiquement africaines aux jeunes Camerounais.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.014
GPT teacher head0.271
Teacher spread0.257 · 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 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
Published2013
Admission routes1
Has abstractyes

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