Does an aggressor's target choice matter? Assessing change in the social network prestige of aggressive youth
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Based on a social dominance approach, aggression is conceptualized as a strategy used to gain position, power, and influence within the peer network. However, aggression may only be beneficial when targeted against particular peers; both victims' social standing and the number of victims targeted may impact aggressors' social standing. The current study examined associations between aggressors' targeting tendencies (victims' social standing and number of victims) and aggressors' own social standing, both concurrently and over time. Analyses were conducted using three analytic samples of seventh and eighth grade aggressors (Ns ranged from 161 to 383, 49% girls; 50% Latina/o). Participants nominated their friends; nominations were used to calculate social network prestige. Peer nominations were used to identify aggressors and their victim(s). For each aggressor, number of victims and victims' social network prestige were assessed. Aggressors with more victims and with highly prestigious victims had higher social network prestige themselves, and they increased more in prestige over time than aggressors with fewer victims and less prestigious victims (though there were some differences across analytic samples). Findings have implications for the need to extend the social dominance approach to better address the links between aggressors and victims. Aggr. Behav. 43:364-374, 2017. © 2017 Wiley Periodicals, Inc.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it