Chance Events and Executive Career Rebranding: Implications For Career Coaches and Nonprofit HRM
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We conducted and analyzed interviews with 20 executives from the for‐profit sector who had transitioned into second careers in the nonprofit sector. Our qualitative study provides an in‐depth analysis of the critical events that triggered career agency and stimulated the change process. At each stage of transition, the executives revisited their personal brands, deciding how to best position their skills, knowledge, and values within the context of their new nonprofit organizations. This research contributes to academic and practitioner knowledge of new career paths open to mid‐ and late‐career executives and insights for nonprofit leadership, as many nonprofits can anticipate major shortages of qualified executives. Each stage in the career transition process provides opportunities for human resource professionals to contribute to successful nonprofit leadership change: first, by creating opportunities for “chance events” motivating transition, followed by career coaching opportunities before and throughout the transition. © 2016 Wiley Periodicals, Inc.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it