“I’ve Been Silenced for so Long”: Relational Engagement and Empowerment in a Digital Storytelling Project With Young Women Exposed to Dating Violence
Bibliographic record
Abstract
Despite decades of research identifying the myriad causes and consequences, young women continue to be exposed to a variety of abuses in their dating relationships. Those who experience such violence often feel shame and isolation and hesitate to reach out for support for fear that their stories will not be heard, respected, or garner appropriate responses. Such abuse often results in grave consequences to well-being and quality of life, with the risk of exposure to one incident of abuse potentially leading to a cycle where young women may be repeatedly drawn to abusive relationships. Finding new ways to expose and disrupt this cycle of abuse in intimate relationships is critical. This article highlights the methods used, specifically an adapted version of digital storytelling as a potential empowerment research methodology with a small group of young women exposed to dating violence. Implementation of this methodology occurred in four phases: providing methodological context, preparing (setting the stage), implementing (constructing and sharing digital stories), and evaluating (experience and impact). Each phase of the methodology is described along with lessons learned to advance the innovative use of digital storytelling in anti-violence research.
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 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 | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".