Regulating Families into Compliance- An Institutional Ethnography of Supervised Visitation in Ontario
Bibliographic record
Abstract
Using ethnographic observation, this research paper investigates the work practices of a supervised visitation site in Ontario. Supervised visitation sites are used by families in high conflict divorces where children and their parents can meet for visits or exchanges under the supervision of “neutral” Staff who document their interactions in observation reports. These organizations are mandated by the Ministry of Children, Community, and Social Services and use discourses that state the environment is safe, neutral, and child-focused. Using Dorothy Smith’s Institutional Ethnography (IE), the researcher adopts the standpoint of a Site Observer or worker faced with the problematic: how can we understand safety, neutrality, and child-focused in locked spaces that require high levels of documentation, surveillance and reporting? Through extensive field notes, I map out the spaces used, the forms workers fill out and where they go, and the reporting structure, with special attention given to the visitation centre’s Service Agreement. My analysis of the ruling relations, that link local activities to institutional power show that the agency is not as safe, neutral, and child-focused as it claims to be. Instead, I discover: (1) safety is synonymous with security, (2) neutrality is enforced through compliance (non-compliance is managed by Staff), and (3) “child-focused” is limited to micro-level interactions. The findings argue that workers engage in multiple, overlapping work processes, identified as documenting, observing, communicating, tracking time/movement, and enforcing/referencing policy. These findings emphasize the need for policy and program changes that are more trauma-informed, choice-based and psychologically safe.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.010 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| 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".