8 Social Hierarchy: The Self‐Reinforcing Nature of Power and Status
Bibliographic record
Abstract
Hierarchy is such a defining and pervasive feature of organizations that its forms and basic functions are often taken for granted in organizational research. In this review, we revisit some basic psychological and sociological elements of hierarchy and argue that status and power are two important yet distinct bases of hierarchical differentiation. We first define power and status and distinguish our definitions from previous conceptualizations. We then integrate a number of different literatures to explain why status and power hierarchies tend to be self‐reinforcing. Power, related to one’s control over valued resources, transforms individual psychology such that the powerful think and act in ways that lead to the retention and acquisition of power. Status, related to the respect one has in the eyes of others, generates expectations for behavior and opportunities for advancement that favor those with a prior status advantage. We also explore the role that hierarchy‐enhancing belief systems play in stabilizing hierarchy, both from the bottom up and from the top down. Finally, we address a number of factors that we think are instrumental in explaining the conditions under which hierarchies change. Our framework suggests a number of avenues for future research on the bases, causes, and consequences of hierarchy in groups and organizations.
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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 | 0.002 |
| 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 | 0.009 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".