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Record W7110607077

Toplu taşıma hizmetlerinde entegrasyon: İstanbul örneği.

2019· dissertation· W7110607077 on OpenAlexaboutno aff

Bibliographic record

VenueOpenMETU (Middle East Technical University) · 2019
Typedissertation
Language
FieldEngineering
TopicUrban Design and Spatial Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPublic transportAction (physics)Variety (cybernetics)Sustainable transportPublic spaceTransportation planningPublic policySpace (punctuation)
DOInot available

Abstract

fetched live from OpenAlex

One of the most important policy and action areas in urban transport planning is the improvement of public transport with a view to increase its usage. Public transport is the most effective way of meeting increasing mobility needs in urban areas. It can provide long-distance journeys that may be difficult to travel via walking and biking. In the face of increasing car usage, it also ensures the most efficient use of space (i.e. transport infrastructure) and hence can help relieve congestion, which is a consequence of increased car usage. Transporting people with public transport, as opposed to cars, also results in lower levels of energy consumption and emissions; and consequently public transport also plays an important role in climate action plans and in achieving such policies as environmentally-friendly, clean, green, energy-efficient, and lower-cost (in terms of space and energy consumption) urban transport systems. Public transport is also a means of providing equal access opportunities to the society, since not everyone can be expected to travel with the car. As a result, for environmentally, economically and socially sustainable urban transport systems, public transport is a fundamental component. Public transport often constitutes a variety of different systems and services; and policies to improve public transport systems bring along a multi-modal system, which consists of various different public transport modes. This improvement also brings along the need for integrated systems. Public transport integration is both a necessity and a key for attracting travelers. Public transport integration has various levels and perspectives that are line/route integration, tariff/ticketing integration, information integration and schedule/headway integration. Integration criteria that are examined in the study are based on literature and three best practice cases from the world. These cases are Singapore, London and Toronto. As a case study, this study assesses public transportation integration in Istanbul, Turkey. Istanbul has a diversity of transit modes, high daily passenger numbers, high population and a high level of mobility. Moreover, maritime transport and diversity of rail transportation (metro, tramway, funicular, streetcar, Marmaray etc.) make Istanbul a good case to investigate the integration of public transportation to compare it with good practice cases. Five transfer stations (Şişli-Mecidiyeköy, Zeytinburnu, Yenikapı, Aksaray-Yusufpaşa, Kadıköy) in Istanbul are investigated in-depth in terms of public transport integration. The aim of the study is to present Istanbul’s situation regarding public transport integration. By doing so, both inadequacies/weaknesses and potentials/possibilities to achieve an integrated public transport system in Istanbul could be investigated and assessed. The findings of the study enlighten the framework of an integrated public transport system, but by taking the locality into account. The study investigates integration components specific to Istanbul and also some transfer stations in Istanbul are analyzed in depth. The study can provide recommendations for future system map, information tools, fare policies and schedule arrangements as well as for achieving the whole system integration.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.835
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.004

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.

Opus teacher head0.021
GPT teacher head0.183
Teacher spread0.162 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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