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Record W7052005717

Regulating Families into Compliance- An Institutional Ethnography of Supervised Visitation in Ontario

2024· other· en· W7052005717 on OpenAlexfundaboutno aff

Bibliographic record

VenueYorkSpace (York University) · 2024
Typeother
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsnot available
FundersYork University
KeywordsEthnographyAgency (philosophy)Participant observationWork (physics)Power (physics)Field (mathematics)Service (business)Tracking (education)State (computer science)
DOInot available

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.824
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.217
Teacher spread0.185 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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