Health Research and Millennium Development Goals: Identifying the Gap From Public Health Perspective
Bibliographic record
Abstract
Assessing the research output within the universities could provide an effective means for tracking the Millennium Development Goals (MDGs) progress. This analytical database study was designed to assess the trend of research theses conducted by the Public Health Department (PHD), Faculty of Medicine, Cairo University during the period 1990 to 2014 as related to the: MDGS, Faculty and department research priority plans and to identify the discrepancies between researchers' priorities versus national and international research priorities. A manual search of the theses was done at the Postgraduate Library using a specially designed checklist to chart adherence of each thesis to: MDGs, Faculty and department research plans (RPs). The theses' profile showed that the highest research output was for addressing the MDGS followed by the PHD and Faculty RPs. Compliance to MDGs 5 and 6 was obvious, whereas; MDGs 2, 3, and 7 were not represented at all after year 2000. No significant difference was found between PH theses addressing the Faculty RPs and those which were not before and after 2010. A significantly lower percent of PH theses was fulfilling the PHD research priorities compared to those which were not after 2010. This study showed a definite decline in research output tackling the MDGS and PHD research priorities, with a non-significant increase in the production of theses addressing the Faculty RPs. The present study is a practical model for policy makers within the universities to develop and implement a reliable monitoring and evaluation system for assessment of research output.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.063 | 0.100 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.027 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".