Embracing the Grey Zone: Navigating flexible boundaries at Welcome Inn Community Centre
Bibliographic record
Abstract
This thesis is an exploration of relationships and issues of professional boundaries at Welcome Inn Community Centre, a faith-based community centre offering programs and services to address issues of poverty in Hamilton, Ontario. Data was gathered through semi-structured qualitative interviews with fifteen staff members, volunteers, and participants at Welcome Inn. A strengths-based perspective combined with mutual relationships and flexible boundaries were found to foster inclusion, acceptance, community building, and personal transformation at Welcome Inn Community Centre; Welcome Inn staff, volunteers, and program participants described these qualities positively. Mixed positive and negative comments were used to describe decision-making and boundaries at Welcome Inn. The need for increased intentionality and clarity around professional boundaries was identified. Using grounded theory methodology, a model, “Embracing the Grey Zone,’ and associated reflexive tools for navigating flexible boundaries were developed. The model and tools are presented here for use in social work community practice and education.
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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 | 0.015 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.034 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".