Breaking the mold: Retention strategies for generations X and Y in a prototypical accounting firm
Bibliographic record
Abstract
Abstract The success of Canadian accounting firms depends on their ability to adapt their long‐standing HR structures and HRD practices to meet the expectations of today's workforce. Generational identity theory and theory explaining employee expectations informed our analysis of a multi‐method (interviews and appreciate inquiry workshops) case study which employed an action research approach. Data were collected from 36 Gen X and Y knowledge workers who were part of the firm's talent pool to determine how closely the work and career expectations of today's (i.e., Generation X and Generation Y) accountants align to the prototypical HR structures and practices of professional partnership (P2) accounting firms. Three main contributions arise out of our qualitative analysis. First, it contributes to generational identity theory by providing a comparison between Generation X and Y in terms of their career and work expectations. Second, it demonstrates why firms with traditional practices and structures may be having difficulty retaining talent in today's labor market. Third, it provides evidence as to why prototypical accounting firms need to change and suggestions on how they can change their HR practices and HRD strategies to enhance retention and better meet the expectations of today's workforce.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".