Meeting learning objectives in an in-house research placement: results of a student-supervisor duo-ethnography
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.
Bibliographic record
Abstract
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.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it