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E-Portals are Valuable Productivity Multipliers, Important Shortfalls in the Safeer System in KSA and Proposed Possible Solutions for Them

2016· article· en· W2823702316 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal for Infonomics · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBig Data and Business Intelligence
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsProductivityComputer scienceEnvironmental economicsEconomicsEconomic growth

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.471
Threshold uncertainty score0.406

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.099
GPT teacher head0.306
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it