Voice, power and discourse: Experiences of participants in family group conferences in the context of child protection
Bibliographic record
Abstract
• Summary: The purpose of this article is to explore the tensions that emerge when two very different discourses – the ‘democratic’, participatory discourse of FGC and the legalistic, bureaucratized discourse of conventional child welfare practice – attempt to integrate. We present the findings of a qualitative study, where we conducted 74 interviews, involving 26 adult family members/caregivers (three youth); six child protection workers; and three FGC coordinators. By listening to the voices of participants, we explore the complexities and tensions that exist at the nexus of (at least) two competing discourses, when the FGC process takes place within the child protection bureaucratic structure. • Findings: Our findings show how participants’ voices were co-opted by the more forceful child protection discourse, itself shaped by legal, bureaucratized, and neoliberal discourses. This research shows how in each case participants’ experience of power was subjugated, even though, in each instance, the case was perceived to have had a successful outcome by the social worker and FGC coordinator. • Applications: If those involved in administering and delivering family group conferencing continue to at least be aware of how power operates in this context, then the possibility exists to realize FGC's broader social justice and transformative goals. Further, a reflective practice ( Schön, 1991 ) can mitigate the possibility of cooptation from particular bureaucratic, legal, and neoliberal discourses which dominate at different times, and which are incompatible with the inherent values and objectives of the FGC.
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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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.019 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".