Digital preservation practices in academic libraries in South Africa in the wake of the digital revolution
Bibliographic record
Abstract
Background: The preservation of digital resources in academic institutions in South Africa is an imperative because of the proliferation of digital resources and the realities of the digital revolution. The study focused on digital preservation practices within academic libraries in South Africa. A number of studies were undertaken in the field of preservation in South Africa and they focused on the preservation of cultural heritage, preservation of electronic government and preservation of public digital information. The major gap in the literature reinforces the need to closely examine digital preservation practices in academic libraries in South Africa. There is a need to understand the extent of preservation of digital resources in various contexts in order to guarantee access to them for future generations. This will improve our understanding of the preservation of digital resources in academic libraries in the wake of the digital revolution. Objectives: The purpose of this study was to investigate digital preservation practices in academic libraries in South Africa in order to suggest solutions for effective digital preservation. Method: The survey research method was used for data collection. Twenty-seven academic institutions in South Africa were surveyed. Data were analysed through the Statistical Package for the Social Sciences. Results: The findings revealed that academic libraries experienced difficulties in preserving and sustaining their digital resources because of the absence of established standards, policies and procedures, inadequate resources, as well as a lack of skills and training. They also had difficulties with limited funding and collaboration efforts, and the threat of technological obsolescence because of the constantly changing software and hardware, poor technology infrastructure and legal issues. Conclusion: All these challenges have created the need for best practices and solutions to facilitate the long-term preservation of digital resources in the academic libraries. Recommendations were made on the basis of the results.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.014 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".