E-Portals are Valuable Productivity Multipliers, Important Shortfalls in the Safeer System in KSA and Proposed Possible Solutions for Them
Bibliographic record
Abstract
E-portal systems play a big role in various countries.They can be deployed by governments and organizations to provide information for citizens and customers and serve their transactions.Consequently, e-portals can be considered as systems that increase productivity of staffs and offer more reliable services.However, many issues have to be solved, such as: privacy and security, performance, reliability, effectiveness, and documents integrity and archiving.We postulate that once the knowhow is acquired for designing and developing one e-portal system, it then becomes readily conducted and adopted by others.In this work, we examine one such e-portal system that is the Safeer system that was designed and developed for the Ministry of Higher Education (MOHE) in the Kingdom of Saudi Arabia (KSA).We believe that this e-portal system could be reconfigured to serve other sectors, such as agriculture, export and import, fisheries, etc.However, before such reconfigurable deployments is possible, it is necessary first to address the shortfalls and gaps that exist in it and could hinder its deployment for other applications.Accordingly, we have examined the Safeer system and identified a possible set of gaps and shortfalls in it.Of these, we have isolated the most three important shortfalls and proposed possible solutions for them.The three shortfalls are: the study plan or the scheduling, the lacking of integrated email server and services, and the lacking of effective integrated archiving system.We believe that the proposed solutions augment the Safeer portal with additional capabilities, and improve its performance, effectiveness, security and privacy, and data and documents integrity; hence, MOHE would be able to license or sell this product.Moreover, we are confident that this work may be of benefit to others in-charge of planning and discharging e-services to their clients.Finally, we conclude this work and establish a set of possible future directions.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".