Examining vulnerability in a dynamic urban setting: the case of Bangalore’s interstate migrant waste pickers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Understanding the causality of vulnerability is difficult to do and consequently has received insufficient attention. Root causes of vulnerability need to be understood and addressed to support adaptation that addresses climate risk and inequality. This paper contributes to this by examining vulnerability from a structural perspective for the case of interstate migrants from West Bengal working as waste pickers in Bangalore’s informal squatter settlements. It also throws light on how understanding structural vulnerability can help to emphasize social justice concerns while adapting to climatic risks. The research, using qualitative methods, examines complex intersections between a multitude of factors such as climate change, agrarian distress, exclusionary patterns of urbanization and the resultant lack of recognition that shapes and reshapes the vulnerability of a certain group of people. Our findings emphasize the compelling need for vulnerability and adaptation research to focus more on understanding inequality if improving justice is a concern. This focus on justice is insufficiently prioritized in climate change adaptation work.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it