Examining the connection between position‐based power and social status across 70 cultures
Bibliographic record
Abstract
Even in the most egalitarian societies, hierarchies of power and status shape social life. However, power and received status are not synonymous-individuals in positions of power may or may not be accorded the respect corresponding to their role. Using a cooperatively collected dataset from 18,096 participants across 70 cultures, we investigate, through a survey-based correlational design, when perceived position-based power (operationalized as influence and control) of various powerholders is associated with their elevated social status (operationalized as perceived respect and instrumental social value). We document that the positive link between power and status characterizes most cultural regions, except for WEIRD (Western, Educated, Industrialized, Rich, Democratic) and Post-Soviet regions. The strength of this association depends on individual and cultural factors. First, the perceived other-orientation of powerholders amplifies the positive link between perceived power and status. The perceived self-orientation of powerholders weakens this relationship. Second, among cultures characterized by low Self-Expression versus Harmony (e.g., South Korea, Taiwan), high Embeddedness (e.g., Senegal), and high Cultural Tightness (e.g., Malaysia), the association between power and status tends to be particularly strong. The results underline the importance of both individual perceptions and societal values in how position-based power relates to social status.
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".