Serendipity and Digital Media Entrepreneurship Teams in Remote Work Ecosystems
Bibliographic record
Abstract
<p>The COVID-19 pandemic has drastically altered and upended the way we learn, work and interact with each other. Human interaction in virtual spaces, specifically video conferencing platforms, has become the “new normal,” and the pandemic will most likely impact how we continue to interact with each other in the future. Serendipity, the notion of accidental information discovery, which often occurs during water cooler moments between team members that fuel some of the greatest advancements in business, technology and medicine, is a phenomenon that is almost non-existent in Digital Media Entrepreneurship remote work ecosystems. This paper aims to explore how social connectivity may help nurture serendipitous interactions in Digital Media Entrepreneurship teams working remotely. I conducted the study using a qualitative questionnaire and a complementary focus group. In addition, I analyzed data using thematic analysis that allowed me to understand the experiences of Digital Media Entrepreneurship teams working remotely.</p>
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".