Bibliographic record
Abstract
Research focused on the relationship between place and health demonstrates that it is complex and shifting, as overlapping social, historical, institutional and political and economic processes continually transform the landscapes in which lived experiences are embedded. Understanding this relationship requires knowledge of the situated meanings and local worlds that ethnographic methods are well suited to investigate. However, even conventional ethnographic methods can be inadequate to capture the embodied, lived experience of place - experiences in which the sensory and inner processes of memory and imagination are often privileged. Accessing these experiences and processes can require more experimental methodological approaches. In this article, I present work from a series of photo essays created between 2011 and 2016 by 15 young people who inhabit the social, spatial and economic margins of Vancouver, Canada, and discuss some of the challenges and opportunities presented by this methodology. Created over 5 years, and broadly focused on how they understood, experienced and navigated their 'place' in the city in the midst of poverty, addiction, violence and physical and mental health crises, the photo essays young people produced are embedded with personal biographies and trajectories, as well as shared experiences of geography, precarity and possibility in Vancouver.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".