Risk factors and missing persons: advancing an understanding of ‘risk’
Bibliographic record
Abstract
Abstract This study seeks to advance an understanding of ‘risk’ for persons going missing—a phenomenon also known as missingness. There is a need to clarify terms used to describe correlations or statistical associations between variables that are identified as risk factors for missing person incidents to understand the mechanisms influencing this phenomenon. Without such research, policies and preventative strategies cannot be adequately offered to begin to reduce missingness. To do so, a review is first provided of the current risk factors identified internationally for missing persons. Then, the Kraemer and colleagues (Arch Gen Psychiatry 54:337–343, 1997; Kraemer et al., Am J Psychiatry 158:848–856, 2001) risk factor classification system and MacArthur framework are applied to the risk factors to identify the ways in which these may be overlapping, proxy, mediating, and/or moderating factors. This clarification on risk terminology attempts to offer a common language for communicating about risk factors associated with missing persons. Suggestions are then provided for how these factors may overlap and/or work together to form risk pathways. The application of this framework highlights that ‘going missing’ may have multiple risk pathways that transgress the current risk factor categorical boundaries. The article then concludes that consistent use of terms and additional research on risk factors will enhance investigations of missing persons and understandings of low- and high-risk groups.
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 | 0.002 | 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 | 0.026 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| 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".