The development of blended friendship in high leader-member exchange relationships: Mechanisms and consequences of a relational shift
Bibliographic record
Abstract
Confusion persists about the overlap between high-quality leader-member exchange (LMX) relationships and personal friendships between a leader and a subordinate. How these notions differ, shift from one to the other, and what their consequences are remain unclear. This paper proposes a framework that examines the fundamental differences between high LMX relationships and friendships. We argue that when high LMX relationships shift toward friendships, they in fact shift toward blended friendships, where the leader and the subordinate concomitantly enact two distinct roles, worker and friend. These blended friendships are qualitatively different from high LMX and from friendships. We detail the process by which blended friendship develops in the context of high LMX relationships and identify the key variables and mechanisms that drive the emergence of such blended friendships. We then examine how subordinates’ well-being, job engagement, performance, and turnover may simultaneously benefit and suffer from their involvement in a blended friendship.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| 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".