Behind Closed Doors: An Osteological Analysis of Intimate Partner Violence
Bibliographic record
Abstract
With an estimated one in three women surviving at least one episode of Intimate Partner Violence (IPV), IPV remains a global issue that disproportionately affects women. While IPV is extensively documented in modern clinical research, detecting skeletal evidence of IPV is challenging. This three-paper thesis addressed the need for a standardized approach to evaluate and recognize skeletal evidence of IPV. Paper One created an osteological protocol for recognizing potential survivors of IPV by systematically scoring skeletal fractures in the areas most often affected during IPV, i.e., the face, chest, and forearms. Paper Two tested the specificity of the new Spigelski and Rogers IPV scoring system, by comparing expected IPV patterning with trauma ascribed to collective violence, i.e., warfare and ritualized combat. Bioarchaeological fracture data was obtained through previously published literature on skeletal samples from the Yucatan (n = 20), Peru (n = 7), and Chili (n = 6). The recorded fractures from the samples were scored and weighted, and the values were used to assess whether IPV patterning was detectable. The threshold values were then compared to a forensic case study involving a domestic homicide victim, with prior documented IPV experiences. Paper Two demonstrated that the fracture patterning associated with IPV differs significantly from trauma patterning associated with warfare and ritualized violence. Paper Three tested whether observed fracture patterning in an adult female sample (n = 59) from the Luís Lopes Skeletal Collection were consistent with IPV patterns, using the Spigelski and Rogers IPV scoring system. Following the observance of healing, bone involvement, and fracture location, six of the 59 females (10%) met the scoring threshold set by the methodology to detect fracture patterning consistent with IPV. This research also highlighted a high prevalence of infraorbital suture(s) within the Luís Lopes sample, a non-metric trait that can be misinterpreted as trauma fracture line(s). Therefore, following the development of a standardized methodology to detect IPV, this thesis has demonstrated that the Spigelski and Rogers IPV scoring system is specific enough to distinguish between IPV and collective violence skeletal fracture patterning, as well as detect potential survivors of IPV in skeletal populations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".