The lived housing experience of the urban poor in Chengdu: Four distinct periods in the urban housing career
Bibliographic record
Abstract
Abstract Current research on the housing careers of urban low‐income groups, dominated by quantitative modelling, has discussed the housing predicament faced by the urban poor at length. While much is known about the factors influencing their housing careers, these studies have failed to provide a satisfactory understanding of the intricacy and depth of human struggles those vulnerable groups experienced in the urban housing market. This contributes a four‐period model, through a dialogue with the established life cycle/life course theories, to the reconceptualization of housing career of the urban poor and depicts a vivid and continuous housing trajectory by analysing their lived experiences at each period. This paper finds that, in a highly constrained and segregated housing market, the housing problems experienced by low‐income earners and their coping strategies are far more complex and variegated than traditional life cycle/course theory would predict. Factors at individual, household, community and even national levels are often interwoven and, more importantly, the combinations of these influences are constantly changing, sometimes repeating along their housing career forming a nuanced dynamism that has been largely overlooked by existing research.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".