Relationships in learning: the role of mentors in the developmental trajectory of law firm associates
Bibliographic record
Abstract
This phenomenological study examines the multiple workplace influences, including mentors and other developmental relationships, on the growth and development of young lawyers from law school through the first few years of practice. The research questions are analyzed through the multiple lenses of situated learning, transformative learning, and mentoring. Situated learning theory directs attention to workplace participatory practices and affordances. Transformative learning theory describes epistemological change. The literature on mentoring and social networks provides a framework to understand the complexity of developmental relationships in the workplace and the effect of those relationships on individual agency. Eleven lawyers in six different large multi-service law firms located in a large Canadian city participated in the research. Three primary methods were employed: an in-depth interview, brief questionnaires on mentoring behaviours and practices, and the Role Construct Repertory Test. Learning occurred within a richly diverse field of influences, including mentors, supervisors, senior lawyers, peers, and clients. These relationships strongly affected the invitational qualities of the workplace, in terms of access to work and support for learning. Mentors were only one member of the constellation of developers and not always the most important influence on individual development. Some participants enjoyed strong and enduring mentoring relationships almost from the outcome of their career, while others struggled without a mentor until later in their career. Formal mentors were more likely than informal mentors to engage in dysfunctional behaviours such as poor communication or limited support. The importance of luck in the workplace was an unanticipated finding. Nearly every participant was able to tell a story about how luck influenced their professional life, either by an early encounter with an important person or access to important work. The participants identified a clear growth trajectory from student through the first three years of being an associate. They described high stress levels and a general feeling of being in over their heads. As they developed confidence and coping skills they described a lessening of the stress and an increasing sense of mastery over their work.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".