Reflections during a global pandemic: Co-creation of research with student partners in a digital environment
Bibliographic record
Abstract
This reflective paper documents the experiences of two students completing a psychology placement for course credit as well as that of staff from the organization they worked at.The students worked together at the same organization during their semester-long placement, which took place during the Winter 2020 term and overlapped with the onset of the COVID-19 pandemic in Ontario, Canada.The partner organization, Teaching and Learning Research in Action (TLR), is a not-for-profit corporation that focuses on effective pedagogy, and the students worked on a study about student wellness and critical reflection.While meetings between the students and staff were initially held in person, approximately midway through the placement all meetings were held via teleconference.This paper includes autoethnographic reflections from the team.Its purpose is to shine a critical lens on whether and how student partnerships can be fostered in a virtual research lab.The virtual classroom can produce effective and enjoyable learning experiences for students (Darby & Lang, 2019), but it can also serve as a barrier to their learning (Bayne et al., 2020).This could analogously extend to learning that takes place in a research lab.Given the scope of this reflective paper, we focus on the following themes: co-creation of research in a digital environment and perceived power dynamics in student-faculty relationships.Through these reflections, we demonstrate the value of learning from each other-through our different roles, our lived experiences in these roles, and our openness to seeking value from all the voices in our project.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | Science and technology studies Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
| grok | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| opus | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.040 | 0.069 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.022 | 0.024 |
| Scholarly communication | 0.026 | 0.012 |
| Open science | 0.005 | 0.047 |
| Research integrity | 0.007 | 0.017 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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 itClassification
machine, unvalidatedLabeled directly by 3 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".