Bibliographic record
Abstract
At the moment of writing, there are two interesting developments related to our common topics of interest.Firstly, we got the announcement that the French Centre for Direct Scientific Communication and the Confederation of Open Access Repositories are collaborating in the development and release by spring of 2022 of a directory of open access preprint repositories [1].It will be interesting to follow this project, as preprints have become increasingly important, particularly during the COVID-19 pandemic, and a directory of this type is indeed necessary and may be very useful.The second announcement is related to the release of the OpenAlex [2] catalog of over 200 million scientific documents, which was named after the Library of Alexandria.OpenAlex features a linked data system based on five entities: works, authors, host locations, institutions and topics.It also facilitates three ways for accessing their dataset: an API, a database snapshot and a website, which is scheduled to go live in February 2022.We open this issue with 'A bibliography of Canadian Inuit periodicals: A case study in Omeka.netmigration', in which Rankin presented the experience, process and best practices for developing an indigenous bibliography website by using the Omeka.netcloud-based service.This included a migration from CSV files, mapping metadata elements under Dublin Core, and using Omeka and TimelineJS.Onyebinama, Anunobi and Onyebinama submitted 'Determinants of research output submission in institutional repositories by faculty members in Nigerian universities', where they analyzed content submission by Nigerian lecturers by university type, discipline, academic qualification, rank and teaching experience.They found that higher submissions came from lecturers within the Social Sciences, also from those with doctorate degrees, those who were senior lecturers, and had from 6 to 10 years of teaching experience.In 'Digital preservation in institutional repositories: A systematic literature review', Barrueco and Termens conducted an interesting review of 21 articles from 2009 to 2020 about digital preservation policies, strategies and activities of institutional repositories.They identified how repositories are achieving long-term preservation and availability of their digital documents.However, they noted a certain bibliographic scarcity, particularly from Europe, which makes it difficult to identify in more depth the implementation of digital preservation.Warraich, Rasool and Rorissa presented 'Challenges and prospects of linked data technology: A qualitative study of Pakistani LIS professionals' insights', where they implemented a phenomenological study to explore linked data-related challenges, prospects and librarians' skills needed for such initiatives to take place in Pakistan.From interviews with 18 librarians, they found that digital library resources' visibility must be increased and the main challenges included implementing MARC standards, a low level of awareness, lack of skills, privacy issues and time constraints.In 'Development and validation of core technology competencies for systems librarian', Naveed, Siddique and Mahmood presented a validated list of digital competencies for systems librarians in Pakistan, organized in six core technological areas and that was developed from their literature review, experts' perspectives and pilot testing.Such core areas included: basic computing, programming and Web publishing, computer
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 | 0.003 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.228 | 0.123 |
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".