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International Organizations and Educational Change in Spain during the 1960s

2020· article· en· W3107189787 on OpenAlexaffvenue
Lorenzo Delgado Gómez-Escalonilla

Bibliographic record

VenueEncounters in Theory and History of Education · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Education in Spain
Canadian institutionsQueen's University
Fundersnot available
KeywordsTechnocracyEliteModernization theoryDictatorshipPolitical scienceAuthoritarianismPoliticsLatin AmericansState (computer science)Economic growthDemocracyPublic administrationPublic relationsEconomicsLaw

Abstract

fetched live from OpenAlex

From the end of the 1950s, Spain’s political leaders felt the need to promote changes in the educational system that would bring it up to date and give more space to practical content and technical training. International organizations played a leading role in the propagation of these new ideas and organizational practices for the training of human capital and its contribution to economic development. The reports and guidelines of the OECD and UNESCO disseminated prior experiences on educational planning carried out in Latin America, at the same time that they functioned as channels for the transmission of knowledge and teaching methods throughout the 1960s. The modernizing sectors of the Francoist elite (the technocrats) were the main liaisons with those international organizations. They were convinced that it was necessary to reform an obsolete and class-based system to adapt it to the demands of a society that was undergoing a strong process of economic growth. Such schemes, likewise, proved useful to the political project of authoritarian modernization that was propping up the Franco dictatorship. This text will examine the relationship of the Spanish state with the international organizations that provided advice and funding to undertake a set of changes in education, changes that would culminate in the General Education Law of 1970 at the start of the following decade.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.881
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.242
Teacher spread0.225 · 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

Citations9
Published2020
Admission routes2
Has abstractyes

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