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Record W3164117859 · doi:10.21608/misj.2021.170590

توظيف الإنترنت في التواصل المعرفي بين الثقافتين العربية والأفريقية

2021· article· ar· W3164117859 on OpenAlexaff
Prof. Ayman Al Sheik

Bibliographic record

VenueMiṣrīqīyā · 2021
Typearticle
Languagear
FieldAgricultural and Biological Sciences
TopicIndigenous Knowledge Systems and Agriculture
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

The importance of the research topic and the reasons for choosing it were the researcher’s visit to some Arab and African countries several times. This made him realize the importance of knowledge communication between the Arab and African cultures in light of the rapid growth of the Internet, in addition to the lack of studies and research concerned with the use of the Internet in intercultural knowledge communication, especially Arab and African culture. The main research question is how the Internet can be employed to enhance knowledge communication between Arab and African cultures. The research sought to achieve several goals, identifying the related concepts and correlational relationships between the Internet, knowledge, culture, Arab culture and African culture; realizing the elements of knowledge communication between Arab and African cultures via the Internet, and the obstacles that hinder this communication. In addition to building a future vision that can enhance the role of the Internet in the knowledge communication between Arab and African culture.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.072
Threshold uncertainty score0.240

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0050.002
Open science0.0000.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0720.024

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 head0.009
GPT teacher head0.179
Teacher spread0.170 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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