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Record W2124544771 · doi:10.19173/irrodl.v9i2.478

Distance Education and Corporate Training in Brazil: Regulations and interrelationships

2008· article· en· W2124544771 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Public Policy
Canadian institutionsnot available
Fundersnot available
KeywordsDistance educationBureaucracyPopulationPovertyEconomic growthDeveloping countryBusinessHigher educationPrivate sectorEconomicsPolitical scienceSociology

Abstract

fetched live from OpenAlex

Distance education in Brazil has evolved more slowly than distance education offerings in other developing countries. This is because all aspects of Brazil’s publicly-funded educational system are excessively regulated, highly bureaucratic, and tightly centralized. Such highly centralized bureaucracy and strict control has resulted in tremendous hurdles that work to thwart the adoption, provision, and diffusion of distance education. This is not good news: Like many developing countries, Brazil is also characterized by wide gaps in wealth distribution, with 20 percent of its population functionally illiterate and living below the poverty line. Distance education, therefore, could be used to help train Brazil’s citizens. Brazil’s emerging status in the global economy, however, is generating enormous opportunities that are fueling demand for change. For example, in their quest to be competitive in the emerging global economy, Brazil’s corporate sector has addressed this challenge by establishing corporate universities to train and educate their employees; much of this corporate training and education takes place online and at a distance. The established and emerging educational opportunities provided by Brazil’s corporate sector, in turn, is fuelling the demand for the provision of distance education throughout Brazil. Indeed, most Brazilians are ready for distance education. Many Brazilian households own television sets and cellular telephones, and its expanding communication infrastructure has capacity to support distance and continuing education models. Moreover, this capacity is currently being used by Brazil’s rapidly expanding corporate university sector. In spite of Brazil’s emergence in the global marketplace and its private-sector educational success stories, Brazil’s public educational institutions have not kept pace. This is due to Brazil’s long-standing stringent regulation of its public education sector. Recent public initiatives, however, such as the Open University of Brazil, do hold promise in fueling the growth of distance education to meet the needs of its citizens, poor and rich alike. This paper analyzes the evolution of distance education in Brazil. It explores interrelationship between the nation’s corporate and publicly-funded higher-education sectors, and the influences Brazil’s highly regulated distance education practices has on the corporate environment. The paper concludes with a broad-brushed overview of ‘success stories’ of Brazil’s corporate universities.

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.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.471
Threshold uncertainty score0.501

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.296
GPT teacher head0.522
Teacher spread0.226 · 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