Maintaining professional competence : impact of organizational and individual factors on the updating activities of public reference librarians
Bibliographic record
Abstract
The purpose of the dissertation is to examine the role of selected individual characteristics and organizational factors in affecting the participation of reference librarians in updating activities to maintain their professional competence in the light of rapid developments in technology. Concerns about the obsolescence of skills of the aging workforce of professional librarians, together with a lack of knowledge about the extent of professional development at the individual level prompted this study. The conceptual framework is based on theoretical foundations in organizational behaviour, psychology, gerontology, education and information studies. The independent variables in the conceptual framework are motivation, barriers to participation, age, professional commitment, updating climate and managerial support. The dependent variable is participation in updating activities. Information on the study variables was collected from 297 reference librarians working in large urban public libraries in Ontario, outside of Toronto, by means of a mail survey questionnaire in Spring 2001. Libraries have an aging workforce: the average age of reference librarians was 46.9 years. Analysis of the data revealed that managerial support was instrumental to participation in both formal and informal activities. Motivation was an important predictor of participation in informal activities. Age, particularly feeling old, and part-time status had a negative impact on participation levels in formal and informal activities. Barriers to participation had a negative effect on participation in informal activities and paradoxically, updating climate had a negative effect on participation as well. This study contributes to a better understanding of the process of maintaining professional competence among reference librarians. The results point to the important role that organizational factors play in the process. A supportive manager is key to librarians' participation in both formal and informal updating activities. Written policies on training and development are needed. The links between updating and rewards need to be emphasized as well as the provision of the appropriate rewards for updating. For older workers, intrinsic rewards are the valued rewards. Part-time status reduces opportunities for updating, yet as libraries come to rely on part-time librarians, their updating needs should be addressed. Finally, providers of formal updating courses should provide distance learning opportunities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".