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Record W2546973172

Factors underlying students’ appropriate or inappropriate use of scholarly sources in academic writing, and instructors’ responses

2013· article· en· W2546973172 on OpenAlexaff
John Sivell

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicAcademic integrity and plagiarism
Canadian institutionsBrock University
Fundersnot available
KeywordsAcademic integrityAcademic writingPsychologyMathematics educationMedical educationPedagogyMedicineSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

At first glance it is surprising that – in remarkable contrast to grammatical or lexical failings which, while certainly not viewed as insignificant, are rarely greeted with outright anger or hostility – inappropriate documentation of scholarly sources so frequently provokes very harsh penalties. Rather than the constructively pedagogical approach that one would expect with regard to other defects in writing, why do we so often witness a rush to negative evaluation of what may, after all, be evidence of nothing more culpable than misinformation, confusion, or oversight? Much has of course been written about possible remedies for ineffective use of scholarly sources and, on the other hand, about available monitoring and punishment for deliberate plagiarism; so, in a sense, the alternatives appear quite simple. However, decisions about when to adopt a more pedagogical or a more disciplinary viewpoint are complicated by difficult and potentially emotional factors that can disrupt calm, confident and well-reasoned judgment. Thus, this paper will focus not on pedagogical or disciplinary strategies, whichever may be considered suitable in a given case, but on a framework for thorough reflection earlier in the thinking process. It will explore multiple perspectives on possible origins for the innocent if maladroit mishandling of scholarly sources, with a view to highlighting a number of informative but potentially neglected reference points – a cognitive psychological perspective on human error and error management, plausible ambiguities in determining what actually constitutes plagiarism, and communication challenges – that may enter into the instructor’s final determination.

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 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)0.006
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.014
Open science0.0040.001
Research integrity0.0010.003
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 head0.483
GPT teacher head0.571
Teacher spread0.088 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations2
Published2013
Admission routes1
Has abstractyes

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