Organizational Identity Work in an Emerging Peer-to-Peer (P2P) Network
Bibliographic record
Abstract
The purpose of this paper is to explore real-time and naturally-occurring processes of emergence of organizational identity from inception. While previous studies provide insights into broader phases associated with identity formation, they do not reveal the potentially more contentious dynamics that are likely to have preceded or underpinned it. With a focus on organizational identity formation in the everyday, this study analyzes 9000 collective e-mails exchanged over four years since the foundation of an organization in the field of open-source hardware. Our study identifies three types of discursive organizational identity work engaged in by members through their interactions, that we call ideological, practice, and boundary work. We show how through their organizational identity work, members continually struggle to reconcile conflicting value commitments with pragmatic concerns about the sustainability of the organization. We argue that while organizational identity is about shared understandings, the capacity of organizational members to develop shared understanding about identity is paradoxically founded on their ongoing everyday confrontations with the tensions underlying it.
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How this classification was reachedexpand
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".