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Record W2099646254 · doi:10.17169/fqs-5.2.615

Research Ethics and Practitioners: Concerns and Strategies for Novice Researchers Engaged in Graduate Education

2008· article· en· W2099646254 on OpenAlexaff
Michelle K. McGinn, Sandra Bosacki

Bibliographic record

VenueForum: Qualitative Social Research (Freie Universität Berlin) · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Science and Policy Research
Canadian institutionsBrock University
Fundersnot available
KeywordsHumanitiesPolitical scienceArtPhilosophy

Abstract

fetched live from OpenAlex

In recent years, practitioner research has gained prominence in academic literature and in graduate programs. This has led to increased attention to the ethical complexities of research that interconnects with professional practice. Many practitioner-researchers struggle to plan research that simultaneously satisfies their intellectual curiosity, the ethical standards of their professional practice, and their institutional research ethics boards. These struggles are particularly evident for new researchers, including those engaged in graduate study. In this paper, we identify ethical tensions for novice practitioner-researchers enrolled in a graduate research course. The paper is intended to contribute to conversations about teaching research ethics in graduate education. URN: urn:nbn:de:0114-fqs040263

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)0.425
metaresearch head score (Gemma)0.363
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.957
Threshold uncertainty score0.709

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4250.363
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0050.005
Science and technology studies0.0450.107
Scholarly communication0.0510.048
Open science0.0090.048
Research integrity0.0430.046
Insufficient payload (model declined to judge)0.0050.003

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 head0.817
GPT teacher head0.670
Teacher spread0.147 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designQualitative
DomainMethods
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

Citations25
Published2008
Admission routes1
Has abstractyes

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