Bibliographic record
Abstract
The initial idea to gather together sero-discordant couples (i.e., when one partner is HIV-positive and the other is HIV-negative) to learn about their experience of living with HIV was generated from conversations that I had with couples at the Southern Alberta HIV Clinic. Beyond the world of HIV medical care, many sero-discordant couples are unable to share personal experiences that might range from travelling and taking their medications, separation due to HIV and exposure, welcoming a child with negative HIV status, and the many other aspects of couples’ lived experiences. My observation was that many sero-discordant couples felt invisible or silenced due to HIV’s social stigma, and perceived that they fell outside of the North American society’s dominant, socially-constructed couple narrative. Multiple services – Alberta Health Services, the Conjoint Ethics Committee, HIV Community Link, the Taos Institute and other community professionals – were engaged to create a community space that would allow sero-discordant couples to come together to share their experience of living with HIV. The aim of this collaborative practice of community engagement was to develop an inclusive, collaborative agenda that would protect and provide a safe space for sero-discordant couples to gather and dialogue. This study was conducted as a participatory action research process that included an initial process of community gathering for sero-discordant couples. The aim was to foster dialogic processes that could be woven together to empower couples to break through the stigma that has kept them marginalized through and after the AIDS epidemics of the 1970s and 1980s. The gatherings were intended to be a first step towards understanding the experience of these couples, which is often invisible, by lifting the veil of marginalization and isolation that has socially permeated their lives since being diagnosed with HIV. This study was conducted over six years. The research phases included the initial gatherings and dialogues, the development of an action-oriented agenda by the serodiscordant community, an engagement of the action phase, and finally the creation of a fully funded, peer-support model that provides individual and group support to the serodiscordant community. This peer support model, as initiated by the action-oriented research process, is now provincially, nationally and internationally recognized as a working model for other oppressed groups of people living with chronic disease (Miller, 2017).
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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 | 0.045 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.052 | 0.036 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.005 | 0.036 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".