Bibliographic record
Abstract
Purpose The purpose of this paper is to examine the competencies, skills and knowledge obtained through a master’s degree in library and information science (LIS) and to identify those competencies that are most valued by graduates who obtained employment in non-library roles. These observations will contribute to an understanding of the transferability of LIS education which will assist LIS professionals and educators to frame LIS competencies in a way that appeals to employers outside of library settings who may not have any knowledge of LIS education or practice. Design/methodology/approach The grounded theory methodology was used with data collection taking the form of semi-structured interviews. Interviews were between 30 and 90 min in length and included career narratives, as well as responses to particular questions about different aspects of professional identity. Participants included graduates of master’s level LIS programs employed in a variety of positions including information managers, policy analysts, human resources specialists, marketers, vendors, taxonomists, search engine designers and information consultants. The participants were employed in sectors including government, information technology, aerospace, oil and gas and retail/online sales in both Canada and the USA. Findings The participants in this study found that their LIS education was valuable to their success in a number of non-library roles. Although the specific career paths of participants were each unique and the different roles they occupied required different combinations of skills, a list of key transferable LIS competencies could be identified. These included a focus on client service, the ability to identify need, and the ability to search for information and navigate databases. In addition, several participants observed that their coursework and opportunities to participate in internships, co-operative positions or work placements prepared them for such workplace conditions as deadlines and fast-paced environments. Originality/value This study involved a population of LIS graduates whose experiences have not been extensively examined in the past. This article helps to fill a gap in the understanding of the professional experiences of LIS graduates who pursue roles outside of libraries. In addition, the semi-structured interview technique allowed for deeper understanding of participants’ perceptions of which of their competencies, skills and knowledge were valuable to employees. This information was gained through answers to specific skills-focused questions intended to identify which competencies developed during their LIS education assisted them most in their careers, as well as larger career narratives. This study will have implications for library practitioners and educators. It will provide insights into valued skills for those who are designing or implementing LIS education programs, as well as LIS graduates who are seeking to market their skills to employers across industry sectors.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.005 |
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".