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Record W4317696172 · doi:10.1080/01609513.2022.2153196

Student research peer support group: reflections on mutual aid in qualitative research

2023· article· en· W4317696172 on OpenAlexaffabout
Ruxandra M. Gheorghe, Sarah Tarshis, Katherine Occhiuto

Bibliographic record

VenueSocial Work With Groups · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsCarleton University
Fundersnot available
KeywordsExperiential learningMutual aidGroup workQualitative researchPeer groupPsychologyPeer supportPedagogySocial workPeer learningGroup (periodic table)Medical educationMathematics educationSociologySocial psychologyMedicinePolitical science

Abstract

fetched live from OpenAlex

This paper details a doctoral student research peer support group that was established consisting of three social work researchers at various stages (doctoral student, doctoral candidate, and postdoctoral fellow) as they trained for qualitative simulation-based research within a research lab at a school of social work in Canada. Grounded in mutual aid, this paper highlights the development of this student research peer support group which focused on experiential, collaborative, and reflective learning. Benefits of establishing similar groups are discussed, and suggestions for doctoral students and faculty interested in developing similar groups are provided.

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)0.207
metaresearch head score (Gemma)0.281
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.207
Threshold uncertainty score0.978

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2070.281
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0210.036
Scholarly communication0.0150.019
Open science0.0070.043
Research integrity0.0110.019
Insufficient payload (model declined to judge)0.0040.001

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 head0.511
GPT teacher head0.647
Teacher spread0.135 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
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

Citations3
Published2023
Admission routes2
Has abstractyes

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