Development and Validation of the Teen Dating Aggression Measure Among Canadian Youth
Bibliographic record
Abstract
Teen dating violence (TDV) victimization is a traumatic experience that can have adverse consequences for adolescents. Current measures that assess TDV do not fully distinguish between psychological and relational forms of aggression, nor do they capture aggressive acts that are common within adolescent relationships. The purpose of this study was to evaluate the psychometric properties of the Teen Dating Aggression Measure (TeDAM) using a sample of 730 Canadian adolescents ( M = 15.88 years, SD = 1.23). The measure is an expansion of the Conflict in Adolescent Dating Relationships Inventory and includes items that describe other forms of violence such as coercion and control, along with more traditional indicators of dating violence (e.g., sexual aggression). Factor analyses yielded three factors, namely psychological aggression, sexual and physical aggression, and relational aggression, which were correlated with more frequent cannabis and alcohol use as well as rape myth acceptance. These results provide initial support for the utility of the TeDAM for assessing TDV with adolescents.
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.
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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 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".