Home All Members of Staff UoN Applying for the Staff Education Support Fund (SESF) Academic Year 2013/2014
Bibliographic record
Abstract
1. (i) Those interested in applying for the above mentioned fund \nshould pay to Income Section Room G4, Kshs.500/= per Application Form. \nOnly permanent confirmed employees of the University of Nairobi are eligible. Do not apply if you do not qualify. \n2. (i) The approved maximum number of beneficiaries per family \nis two (2 only). Where both parents are employees of the University of Nairobi, one parent only should complete the form. \n \nYou should complete a separate form per child for undergraduate Degree programmes only. \n(iii) Those applying for the first time should include copies of Birth Certificates with names of both parents and letters of admission. \n \n(iv) Children MUST not be more than 30 years of age at the time of registration for the degree course, and there should be evidence that the child is dependent on the applicant. \n \n(v) Parents with continuing students should also complete \n fresh application forms for the academic year in question. \n \nYou should produce your receipts at Administration Block Room A307 to be issued with application form/s. \nThe application forms should be completed and returned to the same room A307 not later than 31st December, 2013. \n \n5. The closing date for applying for the Staff Education Support Fund for the Academic Year 2013/2014 is 31st December 2013 LATE APPLICATIONS WILL NOT BE CONSIDERED. \n \n \n \nPROF. HENRY MUTORO \nAg. DEPUTY VICE-CHANCELLOR (ACADEMIC AFFAIRS) \n \nc.c. Vice-Chancellor \n Deputy Vice-Chancellor (A&F) \n Deputy Vice-Chancellor (RPE) \n Deputy Vice-Chancellor (SA) \n All Principals \n All Deans/Directors \n All Chairmen of Departments \n All Registrars (Main Campus) \n All College Registrars \n Managing Directors, UNES \n University Website Administrator \n \n \n7th OCTOBER, 2013
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.819 | 0.656 |
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".