Türkiye’de konut sorunu ve finansman uygulamaları
Bibliographic record
Abstract
Tezin amacı, dönemler itibariyle Türkiye'de ki konut sorununu ve finansman uygulamalarını kapsamlı olarak, sorunun tanımlanması ve uygulanan çözümler yolu ile incelemektir. Çalışmada nüfus, konut ve bankacılık sektörünün verileri kullanılarak Türkiye genelinde illerin ve bölgelerin, genel anlamda Cumhuriyetin ilanından günümüze kadar, spesifik olarak ise 1990-2001 yılları arasındaki dönem itibariyle konut sorunu ve finansman uygulamalarında kaydedilen ekonomik gelişmelerin karşılaştırılması amaçlanmıştır. Çalışmanın sonuçlarına göre, Türkiye'de hızlı nüfus artışı ve şehirleşme ile konut açığı sorunu önemli boyutlara ulaşmaktadır. Konut sorununun çözümünün temelinde düşük nüfus artışı, kırsal kesim-kent arasındaki farklılığın belirli düzeyde olması, yüksek ve ekonomik finansal güç, sosyal adalet, adil gelir dağılımı, ileri teknoloji ve sağlıklı bir organizasyon, kurumsallaşma ve planlama gibi ekonomik ve sosyal özellikler bulunur. Ancak Türkiye'de konut sorununun çözümünü güçleştiren en önemli etken, konut sektörüne üretim ve finansman boyutuyla etkin bir sistemin getirilememiş olmasıdır. Konut sorununun nedenleri gözönüne alındığında konut finansmanı modellerinin; uzun vadeli kredi sisteminin geliştirilmesi ve bankacılık-sermaye piyasası araçları yoluyla sağlanması gerekliliği ortaya çıkmaktadır. Gelişmiş ülkelerde uygulanan uzun vadeli konut finansman sistemlerinin ülkemizde de, bir an önce hayata geçirilmesi şarttır. The objective of this thesis is to study the housing problem and financing practices in Turkey with a comprehensive approach, by defining the issue and the solutions applied. In the study; census, housing and banking sector data have been utilised; and the objective is to compare the economic developments of the cities and regions in Turkey as far as the housing issue and the economic developments encountered in financing practices are concerned; from the declaration of the Republic until the present with a broader outlook specifically between 1990-2001. According to the conclusions of the study, the speedy population increase in Turkey and urbanisation, the magnitude of the issue of the shortage of housing has increased significantly. The economic and social features underlying the solution of the housing issue are low population increase, a certain level of difference between the rural and the urban areas, high and economic financial strength, social justice, fair distribution of income, an advanced technology and a proper organization, conglomeration and planning. However the most important factor rendering the solution of the housing issue difficult is the fact that an effective system of production and financing could not have been brought to the housing sector. When the reasons of the housing problem are taken into consideration, we see the need to develop housing financing models, development of a long term loan system and ensuring these through banking-capital markets. The long-term house financing systems applied in developed countries need to be employed in our country as well.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.036 | 0.005 |
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".