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Understanding change in cities: a personal research path

2007· article· en· W2117009516 on OpenAlexaffvenue
Larry S. Bourne

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsArgument (complex analysis)SociologyStyle (visual arts)Corporate governancePolitical scienceManagement scienceRegional scienceGeographyManagementEconomics

Abstract

fetched live from OpenAlex

At the invitation of the editor, this article offers an overview of my personal research trajectory in one thematic area—the study of urban form, structure and growth. The purpose of the article is not to assign prominence to any particular research style or approach but to illustrate how ideas and priorities in research evolve over a given time period and under specific conditions, as viewed through the lens of my own experience. The article traces the sequential evolution of my research activity and publications from an initial emphasis on understanding change in inner‐city land use and built form, through studies of decision making and the behavioural bases of urban form, to analyses of social change, income inequalities and spatial polarization, and then to issues of planning, policy and governance in emerging city regions. The review highlights lessons learned and concludes with an argument for more inclusive and comparative research.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.994
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.032
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0070.022
Scholarly communication0.0150.025
Open science0.0020.008
Research integrity0.0060.015
Insufficient payload (model declined to judge)0.0050.001

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 head0.119
GPT teacher head0.248
Teacher spread0.129 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2007
Admission routes2
Has abstractyes

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