Marginalized Communities and Social Enterprises
Bibliographic record
Abstract
Thus far, the academic focus has been limited to understand how hybrid organizations balance goal plurality. However, the question how hybrids engage (or fail to engage) local communities in this process and the potential challenges involved has remained unaddressed. Relying on an inductive multiple case study of six Canadian community forest enterprises (CFEs), we describe dilemmas that arise between community engagement and CFEs’ other goals that form their social mission, as well as a distinct set of compromise tactics to address them. We further identify a tension that arises from two distinct dimensions inherent to community engagement that are inherently interwoven yet contradicting. We add to research on paradox by showing that tensions not merely arise between outcome-focused goals that stem from organizational hybridity, but demonstrate that individual goal prescriptions in itself entail elements that cause tension, and warrant paradoxical management to ensure hybrids’ success in fulfilling their overall mission.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.049 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".