Residential preferences, housing affordability and building construction challenges during COVID-19 pandemics: Case study of Belgrade, Serbia
Bibliographic record
Abstract
This paper analyses the impact of COVID-19 pandemic on residential preferences, housing affordability and building construction issues that have been experienced through housing sector in Serbia, especially in the case of its capital city Belgrade. The starting research question is whether COVID-19 pandemic further potentiated the already present socio-spatial issues emerging since the beginning of post-socialist urban transition. The methods used in this study include comparative analyses of statistical data and research findings on housing in the period 1990-2020 and available relevant data and knowledge in this field from the first quarter of 2020 until today. Regarding residential preferences, some recent research showed that the situation of pandemic exacerbated already encapsulated lifestyles and fear from economic recession, as well as it prompted changes of living patterns towards longer duration of staying at home. The pandemic has further disrupted affordability of housing for all social groups, and mostly for the disadvantaged ones. On the other hand, the world pandemic that nobody could predict the end of, has opened up some new opportunities in the construction sector, such as an intensified use of digital technology.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".