Attaining elite leadership: career development and childhood socioeconomic status
Bibliographic record
Abstract
Purpose The existence of disadvantaged sub-populations whose talents are under-leveraged is a problem faced by developing and developed countries alike. Life history data revealed that a large proportion of elite business leaders in the Caribbean emerged from childhood poverty (families subsisting on US$1-2 a day, 40 percent). The purpose of this paper is to examine the key factors supporting the career development of elite leaders from a broad socioeconomic spectrum and both genders in order to build a model of career development for elite leadership. Design/methodology/approach Data were collected via in-depth interviews from a deliberately gender-balanced sample of 39 male and 39 female elite business leaders. Thematic analysis identified consistencies across independent interviews and resulted in a model identifying factors supporting pre-career development as key to eventual attainment of elite leadership. Findings Findings indicated that in childhood and youth, proactivity plus talent recognition and mentoring by adults enhanced access to early developmental opportunities. Early career mentoring guided talented youth to build personal drive, self-esteem, altruism, and integrity, which created a foundation for developing career capital through values-based action. Altogether, these findings indicate the importance of pre-career relational capital to attainment of elite career success. Originality/value Difficult-to-access elite leaders provided rich information emphasizing the importance of pre-career development in childhood and youth to eventual elite leadership attainment. Virtually all of the elites in the sample remember being identified as talented early in life and consider early messages about drive to achieve as well as support received from parents, teachers, and other interested adults to be critical to their success. Hence, a process of talent recognition and encouragement to excel appear to be crucial for connecting young people to important relational capital allowing them to eventually achieve elite status, particularly those individuals hailing from disadvantaged backgrounds.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".