Diversity, Inclusivity, Social Responsibility Aspects, and Outcomes of a Mobile Digital Library and Information Service Model for a Developing Country
Bibliographic record
Abstract
The provision of library services through rigid compartmentalisation of academic, public, school, and special libraries operating in one country can be cost-effective if a country has strong socio-economic, cultural, educational, and political structures. This arrangement is apparently a fallacy for countries that lack such structures, as is the case with Lesotho. This study examined the outcomes and the impact of the UNESCO-funded project titled Distance and Rural Learner-Teacher Support through a Mobile Digital Library (DRULETSMODIL) in Lesotho. The National University of Lesotho (NUL) Library proposed DRULETSMODIL whose objective was to reach out to NUL’s de jure distant teachers and learners. Additionally, the project expanded its scope to include library services to rural and poor communities. This paper outlines how use of the descriptive method, called the corporate social responsibility (CSR) principle, utilised the case study approach to interrogate DRULETSMODIL’s performance. The findings reveal that the project embodied various levels of diversity, inclusivity, and (mainly) social responsibility aspects of providing information for free, to the marginalized communities. From DRULETSMODIL’s three phases covering all the ten districts of Lesotho, positive outcomes were recorded. Through Information, Communication, and Technology apparatuses, DRULETSMODIL’s offerings, and the support of Participatory Initiative for Social Accountability (PISA), diverse information was easily and cost-effectively accessible. The project attracted various partners; beneficiaries included academic library users, secondary schools, and male and female youth and adults in the villages. The study recommends advocacy on CSR for all types of businesses and consideration of this model for developing countries.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".