Reflections From Implementing a Virtual Social Innovation Lab
Bibliographic record
Abstract
Qualitative research methods had to quickly adapt to using online platforms due to the COVID-19 pandemic to limit in-person interactions. Online platforms have been used extensively for interviews and focus groups, but workshops with larger groups requiring more complex interactions have not been widely implemented. This paper presents a case study of a fully virtual social innovation lab on bioplastics packaging, which was adapted from a series of in-person workshops. A positive outcome of the online setting was diversifying the types of participants who could participate. Highly interactive activities such as icebreakers, networking, bricolage, and prototyping were particularly challenging to shift from in-person to online using traditional web conferencing platforms like Zoom. Creative use of online tools, such as Gather.Town and Kahoot!, helped unlock more innovative thinking by employing novel techniques such as gamification. However, challenges such as adapting facilitation for an online environment and exclusion of groups that do not have consistent access to internet and/or computers still need to be addressed. The reflections and lessons learned from this paper can help researchers adapt qualitative methods to virtual environments.
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How this classification was reachedexpand
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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".