‘They’re Very Lonely’: Understanding the Fraud Victimisation of Seniors
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
There are many theories which seek to explain fraud victimisation. In particular, older victims find themselves at the intersection of various discourses which account for victimisation, primarily from a deficit model. This article examines two discourses relevant to older fraud victims. The first positions older victims of crime as weak and vulnerable and the second positions fraud victims generally as greedy and gullible. Using interviews with twenty-one Canadian volunteers who provide telephone support to older fraud victims (all seniors themselves), this article analyses the extent to which these two discourses are evident in the understandings of these volunteers. It finds that volunteers overwhelmingly perceive fraud to occur out of loneliness and isolation of the victim, and actively resist victim blaming narratives towards these individuals. While neither discourse is overly positive, the article discusses the implications of these discourses for the victims themselves and for their ability to access support.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it