Tömeges lakásépítés a világ különböző tájain : merre tartunk? : egy kiállítás tanulságai = Worldwide mass housing, where are we headed
Bibliographic record
Abstract
Világszerte növekvő szükséglet jelentkezik városi lakásokra, különösképpen a városközpontokban. A sürgető igény okozta verseny közepette a beruházók, tervezők sok igen fontos tényezőt figyelmen kívül hagynak, így a közösség, az identitás és az élhetőség kérdését. Bár a világ egyes tájain a nagyvárosok különböző problémákkal szembesülnek, egy kérdés mégis összeköti őket: hogyan lehetne élhetőbbé tenni a városi lakásokat? Hogyan járulhat hozzá a lakások kialakítása a lakók jóllétéhez és életminőségének javulásához? | Summarizing the "Reconceptualizing Urban Housing" exhibition at the 2023 Venice Architecture Biennale, which showcased projects architecture studios, all led by women, addressing the growing global need for urban housing and livability. Despite diverse geographical and cultural contexts (including Uganda, UK, Canada, Malaysia, Mexico, France, Netherlands, Germany, and USA), the featured projects shared a commitment to social and environmental sustainability, exploring approaches to community, identity, and well-being in mass housing. Key themes included contextual sensitivity, the use of local materials and labor, the revitalization of inner cities, the creation of vibrant residential communities, and the balance between private and communal spaces, highlighting a shared ethos in contemporary housing design despite varied local conditions.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".