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Record W2964415892 · doi:10.11591/edulearn.v13i2.6516

Analyzing ethical considerations and research methods in children research

2019· article· en· W2964415892 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

VenueJournal of Education and Learning (EduLearn) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsnot available
FundersQueen's UniversityQueen's University Belfast
KeywordsCommitPsychologyEthical issuesResearch ethicsEducational researchAnonymityEngineering ethicsSpace (punctuation)PedagogyComputer science

Abstract

fetched live from OpenAlex

Research involving children and young people has a particular challenge in comparison to research involving adults. Of this particular challenge is related to the issues of ethical considerations and research methods that the researchers have to commit when conducting research. These are two essential research components and integrally linked to one another because they determine the quality and integrity of the research being conducted. These issues require thorough consideration and implemented differently from the research involving adults. Therefore, this paper aimed to discuss the ethical issues and research methods in researching children and critically evaluate these issues from the research practices by taking the cases of the articles in Teaching English to Speakers of Other Languages. Three articles were selected for further analysis to identify the ways the authors address these issues in their articles. The findings indicated that the authors mainly reported common ethical principles, such as voluntary participation and anonymity, but did not explicitly outline the ethical procedures specific for their children participation in their papers. There was also no indication that they employed appropriate methods to work with children such as using child-friendly methods encouraging children’s participations and giving them space to express opinions and thoughts.

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)0.022
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.570
Teacher spread0.416 · 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