Bibliographic record
Abstract
In 2022, researchers from Loughborough University launched The Meaning of Home Podcast to dismantle stereotypes around homelessness and amplify unheard voices. Hosted by Sara Christou and co-produced with Dave Angel, the series discusses the complexities and connections between home and homelessness in the UK. Each episode centres on a new theme with a roundtable of expert guests, including people with lived experience, frontline staff, artists, and activists. It has been streamed and downloaded thousands of times, not only in the UK but across the world, from Canada to Ukraine. The final episode came-out in August 2024. There are 17 episodes in the series, exploring a range of themes: Episode one: Beginnings Episode two: Empathy Episode three: Visibility Episode four: Belonging Episode five: Voice Episode six: Youth Episode seven: Embodied Episode eight: Choice Episode nine: Displacement Episode ten: Resilience Episode eleven: Discrimination Episode twelve: Change Episode thirteen: Inclusion Episode fourteen: Co-design Episode fifteen: Disparity Episode sixteen: Self-expression Episode seventeen: Final episode The Meaning of Home Podcast was part of The Harnessing Opportunities for Meaningful Environments Centre for Doctoral Training (HOME CDT). This was a cohort of seven Ph.D. projects at Loughborough University approaching concepts of home and homelessness through a creative lens, to build understanding from multiple perspectives. The transdisciplinary team aimed to rethink the relationships between power, policy and the material realities of home and homelessness, to develop impactful new research.
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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.028 |
| Scholarly communication | 0.018 | 0.014 |
| Open science | 0.002 | 0.021 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".