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Record W4389326305 · doi:10.1590/1980-6248-2022-0034en

Authorship construction in the fight against plagiarism: an overview of school research

2023· article· en· W4389326305 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePro-Posições · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicAcademic integrity and plagiarism
Canadian institutionsUniversité Laval
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsExcellenceWork (physics)PolyphonySociologyPedagogyMathematics educationPublic relationsPsychologyPolitical scienceEngineeringLaw

Abstract

fetched live from OpenAlex

Abstract This article presents the results of a doctoral research that assessed how schools of excellence in the city of Rio de Janeiro manage school research and fight plagiarism. Three groups of actors from four schools were interviewed in a semi-structured way: teachers and specialized professionals who work in the 6th to 9th year of middle school and their students. Students declare that: (i) they plagiarize; (ii) do not present works drafted by them; (iii) they buy works from others; (iv) they make paraphrases without citing sources; (v) they make compendiums of quotations from unread works. Also, schools promote authorship construction and plagiarism is a major concern among all professionals. Thus, teachers should pay greater attention regarding an ethical-pedagogical approach when requesting and conducting school research. The work is based on a theoretical framework that values the dialogue between polyphonic voices in constructing authorship, and in fostering the construction of knowledge through school research.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaResearch integrity
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptResearch integrity
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

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)0.014
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.438
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
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 head0.356
GPT teacher head0.483
Teacher spread0.127 · 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