Meta-organizing on the fly in times of crisis: The emergence and morphing of COVID-END
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
Meta-organizations are created to address issues of common concern that require collaboration from various organizational actors. In crisis situations, the bringing together of independent organizations with different roles could be important to support crisis response. In this paper, we draw on a real-time qualitative case study, that of COVID-END (i.e., the COVID-19 Evidence Network to support Decision-making), to examine how and why meta-organizing might emerge, evolve and dissolve (or not) during the lifecycle of a crisis situation. We show how in the midst of a highly volatile crisis, organizations dedicated to promoting evidence-based knowledge were able to coalesce around a common goal, despite prior failed attempts to create a form of collaboration. We call this process meta-organizing on the fly and trace its development over time through periods of emergence, shapeshifting and transition that imply different forms of identity work, boundary work and practice work. We contribute to the literature by showing how an environmental shock can alter the motivational landscape for meta-organizing suddenly and intensely, and we reveal the critical, yet paradoxical role of centralized leadership in enabling it to take form and potentially sustain itself. While inter-organizational rivalry may re-emerge over time, we suggest that meta-organizing on the fly nevertheless has the potential to lead to longer term transformation of organizational relations towards enhanced collaboration, and the recreation of other meta-organizational forms.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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