Bursting bubbles of interiority: exploring space in experiences of distress and rough sleeping for newly homeless people
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
Homelessness is an increasing problem in the UK, which intersects in multiple ways with experiences of mental distress. Within the term ‘homeless’ are contained people in a variety of living situations, including those living in temporary accommodation (hostels, couch surfing, B&Bs) as well those sleeping rough. The latter category is the least common, but on the rise. Between 2010 and 2017, rough sleeping more than doubled in England and Wales, with just under a quarter of total rough sleepers concentrated in London (MHCLG, 2018). Loopstra et al. (2016) argue that the combination of recession and austerity has pushed homelessness upwards, with cuts in welfare spending on social care, housing services and income support for older people most clearly associated with this rise. Of new rough sleepers, around 70 per cent have a mental health diagnosis (NHS Confederation, 2012). This is not just a UK phenomenon; a 2009 population based study in the United States similarly found mental health diagnoses to be three to four times more prevalent in the homeless population (Shelton, Taylor, Bonner, & van den Bree, 2009). This relationship is multifaceted. Both mental health problems and homelessness are argued to be inter-related outcomes of lives characterised by adversity, trauma and abuse (Kim, Ford, Howard, & Bradford, 2010). The relationship is also bidirectional; a distress and mental health crisis can lead to people leaving their homes, while homelessness, with its accompanying insecurity and potential for trauma, can also precipitate, deepen or trigger further mental health problems.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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