Indigenous African-Centred Organizational Change: Building Capacity at a Grassroots B3 Organization
Bibliographic record
Abstract
Nakupenda Community Services (NCS) is a B3 organization based in Ontario Canada. At NCS there are several valuable programs serving the everyday needs of clients. While the services are valued by the community, the internal challenge within the organization is the lack of capacity to lead all programs. Compounding this problem is the demand for more programs and services given the impacts of the recent pandemic. The very active board of directors and employees have made significant efforts to meet the needs of clients, but the problem of capacity persists and negatively impacts service delivery as employees and leaders tend to experience burnout which therefore impacts the retention rate at the organization. The problem of practice being investigated is the lack or organizational capacity to meet outcome expectations at NCS. While funding plays a major role in the lack of human capital the organization possesses, three potential solutions were identified and a merging of two key solutions was selected as the best approach for this Organizational Improvement Plan (OIP). This solution reduces the number of programs being facilitated by the organization and ensures that the programs that remain are managed and lead effectively. To supplement the program reduction, the active participation in a network of Black organizations, identified as a Black ecosystem, is established. Developed through an Indigenous African-centred lens, Ubuntu and highlighting the principles of the Nguzo Saba framework (unity, self-determination, collective-work and responsibility, cooperative economics, purpose, creativity, and faith) collective action will achieve the improvement necessary for NCS.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.011 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".