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Record W3211114679

Youth Participation in Transportation Planning: The City of Toronto’s Youth Engagement Strategy

2020· article· en· W3211114679 on OpenAlexaboutno aff
Liban Mohamed

Bibliographic record

VenueYork University Digital Library (York University) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsnot available
Fundersnot available
KeywordsYouth engagementUrban planningTransportation planningPublic relationsSociologyPolitical scienceTransport engineeringEngineering
DOInot available

Abstract

fetched live from OpenAlex

Utilizing the principles of critical discourse analysis (CDA), I decode the power relations embedded in the 2015 City of Toronto’s Youth Engagement Strategy report to allow for a solid understanding of the framework used by planners in their proposed “engagement” with youth and in (dis)locating “transportation” in their planning (or non-planning) for youth. With the report stating transit and transportation as the leading issue the youth care about, I argue the misconception that the youth of today are not concerned with transportation planning. The traditional adult-oriented approach to transportation planning has served the youth by default, and this is very concerning. The youth deserve to be invited into the decision-making process as well as informed as to the impact of their participation. We cannot call for youth participation if that participation does not have meaning. The City of Toronto’s Planning Division needs to invite youth voices if they are prepared to listen to them. Youth participation is a promise we make to young people. Their idealism, strength, and creativity are a gift to us, and we need to treat it as such.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.459
Threshold uncertainty score0.592

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 communication0.0000.002
Open science0.0010.000
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 head0.072
GPT teacher head0.238
Teacher spread0.166 · 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 designQualitative
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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