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Record W4205308108 · doi:10.1080/02615479.2021.2021173

Meeting learning objectives in an in-house research placement: results of a student-supervisor duo-ethnography

2022· article· en· W4205308108 on OpenAlex
Kimberly A. Calderwood, Larissa N. Rizzo

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

VenueSocial Work Education · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsTrent University
Fundersnot available
KeywordsSupervisorEthnographySociologyPsychologyMedical educationPedagogyMathematics educationMedicinePolitical scienceLaw

Abstract

fetched live from OpenAlex

To address a shortage of social work placements during the COVID-19 pandemic, the first author created a remote in-house research placement providing a third-year undergraduate student with 240 field education hours to count toward a Bachelor of Social Work degree. The primary task was for the student to analyze interview transcripts about the experiences of students and trainers in an online counseling skills workshop. Using a duo-ethnographic method, the findings showed that the student-supervisor relationship was key to the learning, there were challenges in aligning the tasks with the range of learning objectives expected in the program, and several of the expected and unexpected learning outcomes achieved were considered transferable beyond just research skill development. While there were some challenges related to isolation, exhaustion, and self-care, overall this placement was considered to be a success. Recommendations for future research and in-house placements were made.

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)0.010
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.006
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.097
GPT teacher head0.491
Teacher spread0.394 · 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