PEER-BASED OUTREACH WORKERS AS AGENTS OF SOCIAL COLLECTIVE CHANGE
Bibliographic record
Abstract
Place is not a static backdrop for social relationships; rather, it is a dynamic product of the interactions among the people, practices, objects, and representations contained within it. Often, street-involved people who use drugs are excluded from interactions that would otherwise allow them to participate in community dynamics. In Vancouver, British Columbia, peer-based outreach groups redress these barriers by providing low-threshold positions to individuals living with active or past addiction. The overall question of this thesis is: what is the role of place in the health of an individual and of a community? Objectives include: (1) applying existing models of social exclusion to outline barriers preventing Peer Members from engaging in placemaking; (2) mapping the ideological positionality of the Peer Members and the rest of the community with regard to citizenship; and (3) exploring how Peer Members utilize their biosocial role as outreach workers to establish social capital and situate themselves as participants in a healthy community. By providing a platform where various social identities can interact with one another, ties of familiarity are established between these groups, thus enabling the transfer of resources, knowledge, and shared norms of respect. The first half of the discussion focuses on how social and geographic displacement legitimizes the process of social abandonment. Consequently, this relegated the Peer Members and their peers into the role of anti-citizen, rationalized their marginalization, and reinforced the wider community’s stigma toward people who use drugs. The latter half of the discussion illustrates how the Peer Members utilize their biosocial role of outreach and support workers to navigate boundaries and establish social connections to circulate knowledge and information within and among different social fields. This enabled the expression of mutual reciprocity, thereby negotiating the place of people who use drugs and harm reduction among the wider community. Place is therefore a concept that shapes, and is shaped by, the social networks that determine social legitimacy or illegitimacy. Although marginality and oppression cannot be transformed immediately, creating a social environment where Peer Members can be supported and support one another helps mitigate the marginalization that characterizes their lives.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.061 | 0.005 |
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".