Exploration of LIS professionals efforts in Pakistan towards the improvements of technological competencies in 21st century
Bibliographic record
Abstract
Purpose The purpose of this qualitative study is to investigate/review the skills required for library and information science (LIS) professionals in the 21st century and to propose an alternative approach as the suggested key skills. Design/methodology/approach Twenty-two LIS professionals from Pakistan were interviewed, and 10 LIS professionals were from abroad, including two from the USA; six respondents were from Saudi Arabia; one from Canada; and one from Malaysia. In-depth interviews with faculty members were conducted to ascertain their perceptions of the knowledge and skills necessary to be competent in delivering quality education to the future information breed. Findings The findings emphasise the importance of a variety of competencies for librarians and information educators, including subject knowledge and skills; information technology knowledge and skills; instructional skills; research skills; and managerial, leadership and social skills. Additionally, it was noted that LIS professionals require a diverse set of skills that should be fostered by educators and employers. By promoting these in the broader community, the author can encourage the next generation of LIS professionals to consider LIS as a viable career option. Originality/value The findings presented in this paper provide a unique window into the country’s workforce needs. Though the study was conducted from a Pakistani perspective, the findings may have implications for other countries with comparable circumstances, including social impact. It also provides a new analysis of the selected generic and LIS skills that can be communicated in an innovative manner to prospective LIS employees, employers and educators.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".