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El código disciplinar de la historia escolar en España: Algunas ideas para la explicación de la sociogénesis de una materia de enseñanza

2008· article· en· W1984214734 on OpenAlexvenueno aff
Raimundo Cuesta

Bibliographic record

VenueEncounters in Theory and History of Education · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Education in Spain
Canadian institutionsnot available
Fundersnot available
KeywordsDisciplineHumanitiesElitismNationalismSociologyTechnocracyPolitical sciencePhilosophyLawSocial sciencePolitics

Abstract

fetched live from OpenAlex

This paper explains the heuristic potential of the concept of disciplinary code, when applied to the study of the sociological origins of History teaching in Spain. The disciplinary code of History as a subject – seen as an invented social tradition – began in the middle of the nineteenth century. Its main features – archaism, nationalism, elitism and rote learning – survived during the period of traditional-elitist education model, which lasted in Spain until the 1960s. It went through a revision process, more apparent than real, under the education reforms of 1970 and 1990 a period in which the technocratic mass education model prevailed. Traditional teaching styles continued while reforms were being implemented. They prevail with even greater strength today, reaffirmed by conservative education policies, which aim at a tighter control over the curriculum, by returning to the old norms of the disciplinary code.

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)0.004
metaresearch head score (Gemma)0.005
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 score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0020.019
Scholarly communication0.0090.005
Open science0.0010.003
Research integrity0.0020.002
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 head0.011
GPT teacher head0.286
Teacher spread0.275 · 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

Citations5
Published2008
Admission routes1
Has abstractyes

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