Kortteli 3.0 - Kortteliuudistuksen periaatteita Tampereen keskustassa tyyppikorttelin avulla
Bibliographic record
Abstract
In my master's thesis I study the principles of urban block renewal with the help of a case study block. The case study block is in Tampere city center. The demolished wooden perimeter blocks from 1960's onwards in many cities in Finland were replaced by building types more common in high-rise suburbs. This has produced loose cityscape with dreary courtyard-milieu and inefficient environment comparing to traditional European city centers. Because of this the urban life has partly suffered as well. The buildings that replaced the traditional wooden block are now in an age where they are in a need of major renovations. Supplementary building is a good way of covering the costs of renovations and at its best; it can produce new kind of urban life in city centers. Considering urban block renewal, thesis deals with. - Supplementary building on the edges of the perimeter block (infill), roofs and lofts, aboveground basement floors and courtyards. - Building an underground common parking house for the whole block. - Common green area in the courtyard. Thesis seizes with legal and economic themes considering the problematic of an urban quarter consisting of several housing cooperatives. Also, a challenge is to make the renewal tempting for housing cooperatives that are unwilling for change. How big of an economic benefit can a housing cooperative receive if they sell unused parts of their plot for new buildings -can it cover the costs of for instance the underground parking house or renovation? What is the value of the plot for an investor or a building company for the project to still be worth investing? Additionally, there will be suggestions for the city council to enhance their role as an assistant for supplementary building to happen, especially concerning parking regulations. After studying various massing alternatives for supplementary building, I was convinced that the costs of underground parking house can be covered with it. In many cases the renewed block was more pleasant than without supplementary building, although it loses some open space. By combining different options can there be enough potential income for housing cooperatives to save for renovation also. The end result is a cosy place to live - and that presumably also adds to the value of the existing apartments.
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 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) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.071 | 0.083 |
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; both teacher heads agree on what is shown here.
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".