Balancing exploration and exploitation in alternative work arrangements: a multiple case study in the professional and management services industry
Bibliographic record
Abstract
Abstract In this inductive study we investigate the local context surrounding professionals choosing to work on a reduced‐load basis. We analyze qualitative data collected from key individuals (spouse, boss, co‐worker, and HR manager) composing a network around several professionals working reduced load in the professional and management services industry. We describe the interactions in this network using the concepts of exploration and exploitation in four contexts (organization, workgroup, individual, and family). We also identify three emergent patterns of cross‐level distribution of exploration and exploitation across contexts, labeled Solo Performance, Organic Fluid Adjustment, and Orchestrated Cooperation. Each of these patterns illuminates a specific form of interaction between the dynamics of exploration and exploitation across contexts. We examine the different outcomes of each pattern for the organization, the individual, and the family. Implications of the findings for theories of work‐family interaction, organizational learning, and the organization of work in the professional and management services industry are discussed. Copyright © 2008 John Wiley & Sons, Ltd.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".