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Record W7120599926

Formar para a sala de aula longe da sala de aula : a expansão neoliberal da educação, regulada pelo Estado, por meio das licenciaturas EAD

2025· dissertation· pt· W7120599926 on OpenAlexaboutno aff
Daniê Regina Mikolaiczik

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2025
Typedissertation
Languagept
FieldSocial Sciences
TopicEducation Pedagogy and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationExploratory researchState (computer science)Qualitative researchDistance educationRationalityHigher educationBasic education
DOInot available

Abstract

fetched live from OpenAlex

The figures for undergraduate degree programs show that, currently, the majority of Brazilian teachers obtain their degrees from for-profit institutions and through distance learning. The National Education Guidelines and Bases Law (Law No. 9,394 of 1996) is crucial in defining this scenario, as it regulates, for the first time, distance learning in undergraduate programs. The general objective of this thesis, through an analysis of educational legislation, was to identify and problematize the State's responsibilities in the expansion of distance learning undergraduate programs. The aim was to examine whether or not there were markers of neoliberal rationality in the legislation that enabled the growth of distance learning in initial teacher training programs for Brazilian teachers. The research problem was defined as follows: "Since the State is the regulator of educational policies for Brazilian higher education, what interests and rationales underlie the expansion of distance learning undergraduate programs?" Methodologically, the research was characterized as basic in nature, exploratory in terms of objectives, qualitative in terms of the approach to the problem, bibliographical and documentary in terms of procedures. The basic theoretical framework was Dardot and Laval (2016), Ball (2022) and Bourdieu (2015), among others. Ten pieces of legislation dealing with distance education and undergraduate courses were selected, and the categories of privatization and flexibilization were used for the Content Analysis of the documents. The thesis was anchored in the following methodological triangulation: a literature review, a State of Knowledge review of theses on the topic, and the legislation studied. The main findings of the research indicated that the State, through complicit educational legislation, allowed—and even encouraged—the predominance of distance learning: a teaching modality, especially that offered in for-profit institutions, that reproduces inequalities compared to higher education by maintaining historical and structural distances; it promotes the erosion of academic relationships, the destruction of collective forms and democratic principles, as it prepares individuals who normalize the exchange of stability for precariousness disguised as flexibility, of solidarity for isolation; it fosters an economic, cultural, and political transformation in education, as it turns higher education into a business, bases curricula on the dictates of the market and performativity, and replaces collective interests with competitive relationships, in which the focus is on production, even if lacking depth.

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)0.006
metaresearch head score (Gemma)0.009
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 score0.024
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.007
Scholarly communication0.0060.003
Open science0.0010.004
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 head0.046
GPT teacher head0.343
Teacher spread0.296 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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