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Record W7065231163

Design and Integration of Transit-Oriented Development in Transportation Education

2020· article· en· W7065231163 on OpenAlexaboutno aff

Bibliographic record

VenueBucknell Digital Commons (Bucknell University) · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumOrder (exchange)Engineering educationQuarter (Canadian coin)Sustainable developmentCurriculum developmentHigher educationCourse (navigation)
DOInot available

Abstract

fetched live from OpenAlex

Transit-oriented development (TOD) is an effective planning strategy that has continued to gain interest for over a quarter century since the term has been coined. TOD is a mixed-use development that concentrates on connecting spaces and infrastructure around successful transit service in order to provide high mobility. To prepare for continued implementation, TOD needs to be fully integrated into curricula to expose and attract the next generation of transportation engineers and planners. This study focuses on an evaluation of existing TOD pedagogical efforts across the nation in order to identify the level of integration. A survey is conducted on higher education programs throughout the United States in order to provide an update on module versus full course level integration and determine existing pedagogical methods/resources used in the classroom. In addition, a case study application focused on the development and implementation of a TOD module to a sustainable transportation engineering course at Bucknell University is provided with the goal of integrating the module into similar courses throughout the country.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.433
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.188
Teacher spread0.168 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2020
Admission routes1
Has abstractyes

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