A review of uncleared missing person cases and police responses in Alberta
Bibliographic record
Abstract
Research into the topic of missing person cases in Canada indicates a gap between understanding the complete extent of this issue and the police response to such cases. Within the Canadian policing community, it is evident that there is a consensus regarding the value in developing a national missing persons program that would include a national database, a national public website, streamlined policies and investigational procedures, and strategic partnerships. However, it is not yet clear how such a program would be developed and sustained. Presently, there exist isolated Provincial responses to this most important topic. This major paper will focus on the Province of Alberta and examine the extent of uncleared missing person cases and the associated police responses. This research commenced with a review of available statistics on uncleared missing persons cases in Alberta in an effort to provide an accurate reflection of the current state of uncleared missing persons cases in the Province. The research then examined the associated police responses and concluded with a discussion centering on the matter of how police respond to missing persons cases in Alberta. Recommendations from this paper have already been implemented in Alberta and others are being further considered for use across Canada.
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 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 | 0.022 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.023 | 0.040 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".