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Brazilian Higher Education in the 1960s and 1970s of the 20th Century: International Agreements and the Reform of the Brazilian University

2020· article· en· W3115680882 on OpenAlexvenueno aff
António Gomes Ferreira

Bibliographic record

VenueEncounters in Theory and History of Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Pedagogy and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceEconomic historyEconomics

Abstract

fetched live from OpenAlex

After World War II, cooperation agreements in the educational area were signed between Brazil and the United States. However, from the 1960s, there was a closer relationship between the two countries, with new agreements signed between the Ministry of Education (MEC) and the United States Agency for International Development (USAID), known as the MEC-USAID Agreements. This study’s objective is to analyze the influence of the MEC-USAID Agreements on the reform of the university approved by Law 5.540 / 1968, which established norms for the organization and functioning of higher education. Regarding the methodology, it is a documentary and bibliographic study. The results indicate that although there are criticisms of the agreements, there is no denying that they had influence on the 1968 reform, mainly regarding the cathedra extinction as well as the teaching career institution and the adoption of the departmental regime and credits in subjects. In addition, the university structure established by Law 5.540 / 68 remains virtually unchanged to this day.

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)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.993
Threshold uncertainty score0.259

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0070.007
Scholarly communication0.0050.002
Open science0.0000.002
Research integrity0.0010.002
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 head0.016
GPT teacher head0.303
Teacher spread0.288 · 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.

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

Citations3
Published2020
Admission routes1
Has abstractyes

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