استراتیجیات استخدام شبکات التواصل الاجتماعى فى الأرشیفات الوطنیة العربیة : دراسة وصفیة تحلیلیة
Bibliographic record
Abstract
In recent years, Archives have used large-scale social networks formultiple purposes to enhance the role of users and followers’ participation byreceiving their suggestions that support the development of information servicesand Archives' activities. Although the use of social media (Facebook, YouTube,Twitter, LinkedIn, Instagram, Flickr, Templer, …) is a relatively new phenomenonin Archives compared to libraries and other information centers, NationalArchives have sought to adopt strategies to use social networks to increasecommunication and interaction with users and to identify their views in thedevelopment of information services provided, including interactive contentcreation and distribution of content related to archival documents.This study aims to identify the uses of social networks in the ArabNational Archives, the availability of specific and declared strategies for their use,the analysis of their characteristics (objectives, content, …etc.), the socialplatforms used by archives and the training of staff who manage and update thecontent of National Archives on these platforms. The study relied on theanalytical descriptive approach to describe the use of Arab and foreign archivesfor social networks and the content analysis methodology to analyze thecharacteristics of national archives’ strategies for the use of these networks.The study included (12) Arab National Archives; in addition to (5) ForeignArchives (USA, Canada, Australia, United Kingdom, France) to benefit from theirstrategies in using social networks. Among the most important proposals of thestudy is the need to develop a social media strategy in the Arab NationalArchives, to diversify the archival content on social media and to form a socialmedia teamwork responsible for planning and implementing the Archives'strategy for social media. The study suggests also that the National Archives startan advanced strategy focused on the context, depth and quality of the use ofsocial media. In addition, they should develop a marketing plan, focusing on afew social platforms to improve the presence of the Archive in the community andto raise awareness of its role. The social media teamwork in the Archive shouldensure that the Archive updates the content of its social platforms regularly especially those with a large number of subscribers and followers, andparticipates actively in the conversations of followers and users of the Archive’ssocial platforms. They should archive models of users' participation on what ispublished and shared concerning the archival content on social platforms,especially on important national events.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.130 | 0.079 |
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".