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Record W4308948109 · doi:10.5753/wie.2022.225771

Tutorial para Futuras Cientistas: Um Relato de Cursos para a Disseminação da Participação de Mulheres na Área de Computação

2022· article· pt· W4308948109 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.

fundA Canadian funder is recorded on the work.
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

Venuenot available
Typearticle
Languagept
FieldDecision Sciences
TopicBusiness and Management Studies
Canadian institutionsnot available
FundersCanadian Bureau for International Education
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Vários são os estudos na literatura que apontam o público feminino como minoria nos cursos superiores da área de Tecnologia da Informação. Como consequência, inumerosas iniciativas surgiram para incentivar a entrada de mulheres para essas carreiras. Este artigo relata a elaboração de uma atividade de tutoriais, com um conjunto de minicursos estratégicos, na oitava edição do Encontro Acadêmico de Computação (EAComp), organizado pelo Programa de Educação Tutorial (PET) da Universidade Federal do Maranhão em 2021. O objetivo foi atrair o público feminino ao ingresso acadêmico no curso de Ciência da Computação. Também, este artigo apresenta a percepção das participantes sobre o impacto dessa atividade para o aumento e integração de mulheres no espaço acadêmico.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0020.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.154
GPT teacher head0.404
Teacher spread0.250 · 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

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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