Social media “ghosts”: how Facebook (Meta) Memories complicates healing for survivors of intimate partner violence
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
This paper contributes to feminist conversations about algorithms and design justice by examining ways Facebook’s (Meta) Memories affordance, when it draws on previously posted photographs of abusive former partners, is problematic for gender-based violence (GBV) survivors. With analyses drawn from semi-structured interviews with twelve “survivor-users” and a walkthrough of Memories’ settings to better understand what opportunities users have to control this function, this paper finds that Memories triggers survivors, makes their abuser seem inescapable and reduces survivors’ sense of agency, among other challenges to their well-being. By extending abusers’ intimidation back into survivors’ lives, Memories unintentionally supports perpetrators’ aims: to scare, isolate and punish their targets. This paper concludes that a masculinist bias within Memories’ design leads to painful consequences for survivor-users of varying identities. Ultimately, this study proposes possible means of addressing Memories’ challenges for survivor-users, including the option for users to opt in to, rather than out of, the function in the first place; alterations to Memories’ interface to enable the immediate flagging of problematic content; and continued movements towards trauma-informed design practices in the technology sector.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it