The Effect of Global Economic Crisis on Service Delivery in Selected Non-Governmental Organizations in Kenya
Bibliographic record
Abstract
This study explored the effects of global economic crisis on service delivery in selected non-governmental organisations (NGOs) in Kenya. It was of the view of the researchers that NGOs must have experienced the effects that were brought about by the Global Economic Crisis (GEC) and must have had alternative methods that were used effectively. A number of challenges were faced such as reduction in project implementation, operation scale-down, budget reduction, decreased funding, employment freeze and staff turnover. Service delivery on program activities were affected in various ways such as reduction in staff which in turn scaled down on operations. Main management strategy employed was restructuring. The study recommends that NGOs need to focus on diversifying sources of funding. NGOs should find creative and innovative ways of not only surviving such times but also even possibly seizing them as an opportunity and make a significant difference. Raising awareness among stakeholders, developing agreements among management and staff on clear criteria and measures to manage reserves, unrestricted funds and investment decisions can be utilized.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".