Apoema: Exploring a communally constituted conception of selfhood approach to child welfare through an Indigenous Family Group Conferencing program
Bibliographic record
Abstract
Canadian child welfare systems can be neatly mapped onto individualistic conceptions of selfhood.This individualistic stance is ingrained in child welfare's framing of child maltreatment, language, and interventions as connected to parents' unwillingness or inability to make proper and responsible choices.What follows is a series of adversarial and punitive attitudes and practices that normalize defamilialization and emancipation of children and youth from their families, without taking into account circumstances that precipitate the involvement of child welfare systems in families' lives and the narrow and/or non-existent avenues for self and social improvement available to them prior to involvement.Based on a previously articulated critique of selfhood, this dissertation reaffirms the need for ontological reformulation concerning the nature of selves, offering the communal self as an alternative.This communally constituted, relational, and historical and socio-culturally situated concept of self, acknowledges the interplay of agency and context from a critical lens.It aligns with Indigenous notions of self-inrelation and Indigenist scholarship and advocacy that for decades have urged child welfare stakeholders for more broadly defined notions of selfhood and family.The communal self also grants a space wherein non-Indigenous child welfare stakeholders can ethically position themselves and engage in ally-ship without disingenuously trying to occupy Indigenous perspectives.Through an exploratory qualitative study of the experiences of families and mentors involved with an Indigenous, community-led and based Family Group Conferencing child welfare program in Winnipeg, Manitoba (MB), this dissertation goes beyond theorical considerations, providing a concrete example of the promise of child welfare interventions offered from a communal perspective of selfhood.Mentors, parents, and community members voices' enliven the Tupi term that precedes the title of this dissertation, apoema, or "the one who sees far", compelling us to see beyond the immediacy of what surrounds us, to conceive of ways to recast a more harmonious future, not only for Indigenous but for all peoples.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.033 | 0.019 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".