Is competence without humility wasted in building the trust necessary for knowledge transfer in younger/older worker dyads?
Bibliographic record
Abstract
Purpose Successful knowledge transfer (KT) between younger and older workers (YW and OW, respectively) is critical for organizational success, especially in light of the recent surge in employment volatility among the youngest and oldest segments of the workforce. Yet, practitioners and scholars alike continue to struggle with knowing how best to facilitate these exchanges. The qualitative study offers insight into this phenomenon by exploring how KT unfolds in YW/OW dyads. Design/methodology/approach The authors performed a reflexive thematic analysis of semistructured interviews with two samples of blue- and white-collar younger/older workers from the USA ( N = 40), whereby the authors interpreted the “lived experiences” of these workers when engaged in interdependent tasks. Findings The analysis, informed by social exchange theory and exchange theories of aging, led to the development of the knowledge transfer process model in younger/older worker dyads (KT-YOD). The model illustrates that, through different combinations of competence and humility, KT success is experienced either directly (by workers weighing the perceived benefits versus costs of KT) and/or indirectly (through different bases of trust/distrust perceived within their dyads). Further, humility in dyads appears to be necessary for KT success, while competence was insufficient for realizing KT success, independently. Originality/value In exposing new inner workings of the KT process in YW/OW dyads, the study introduces the importance of humility and brings scholars and organizations a step closer toward realizing the benefits of age diversity in their workplaces.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| 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".