The healthcare system in Africa: the case of guinea
Bibliographic record
Abstract
Background: The aim of this article is to review the health system of Guinea from its past period to its recent period. The article gives an overview of the general situation of the country. It presents the political; economic, social situation of Guinea. It briefly addresses the country’s situation before its independence and goes on to describe its health situation from its independence on October 2nd, 1958 to 2014.Methods:This article is both retrospective and prospective. It highlights some epidemic diseases such as the Cholera, which has become almost endemic in the country. It also describes the current burden of diseases in the country.Results: The environment is a factor contributing to the health issues in the Republic of Guinea; among others, we can list unsafe water, hygiene, and excreta disposal; urban air pollution; and indoor smoke. This article shows that the current health issues in Guinea are due to the above factors. The Ebola outbreak is an illustration of the Global Health problem that started in Guinea in 2014.Conclusions:At the end of this article, changes and improvements to the healthcare system in the Republic of Guinea are proposed.
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 | 0.001 | 0.002 |
| 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 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 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".