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Record W3194751497 · doi:10.1177/03400352211031577

A review of the library and information science profession in the Maldives: Development, challenges and opportunities

2021· review· en· W3194751497 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

VenueIFLA Journal · 2021
Typereview
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsBrampton Civic Hospital
Fundersnot available
KeywordsGovernment (linguistics)Action (physics)Information scienceDeveloping countryPublic relationsLibrary scienceState (computer science)Political scienceSociologyEconomic growthComputer scienceEconomics

Abstract

fetched live from OpenAlex

The Republic of Maldives, a small island developing state in the Indian Ocean, has achieved upper-middle-income and high human development category status, and one of the strongest information and communications technology infrastructures in South Asia. However, the country’s library and information science sector, which saw its inception over seven decades ago, has yet to advance beyond the initial development phase. This article traces the emergence of the library and information science sector in the country and draws attention to the myriad challenges faced by it. The article is also an attempt to draw the attention of government decision-makers and motivate them to understand and resolve the difficulties faced by the library and information science sector through engaging library and information science employers, educational institutions, professional trainers, and library and information science professionals. Some concerns are identified and five key action areas with associated action steps are suggested. These may resonate with other small developing countries that are facing similar scenarios.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.937
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.034
Open science0.0010.000
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 head0.140
GPT teacher head0.368
Teacher spread0.229 · 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