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Record W2888725046 · doi:10.1111/cag.12484

Living in Old Montreal: Residents’ perceptions of the effects of urban development and tourism development on local amenities

2018· article· en· W2888725046 on OpenAlexafffundvenueabout
Priscilla Ananian, Ariane Perras, Marie‐Axelle Borde

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsUniversité du Québec à Montréal
FundersFonds de Recherche du Québec-Société et CultureMitacs
KeywordsTourismGentrificationGeographyPerceptionImpacts of tourismUrban planningPopulationEconomic growthSocioeconomicsTourism geographySociologyPsychologyCivil engineeringEconomics

Abstract

fetched live from OpenAlex

Abstract Urban development and tourism development have transformed urban environments within older neighbourhoods. While urban policies highlight the necessity of developing housing and mixed land use in tourism districts, previous studies have shown local effects of tourism and gentrification. In this paper, we focus on residents’ perceptions of the effects of urban and tourism development on local amenities such as shops, local social infrastructure, and public services. Our case study is the Old Montreal district, the population of which has more than tripled since the 1980s. We conducted a survey with 331 residents, and 20 semi‐structured interviews, analyzing their perception of Old Montreal as a place to live and their use of local amenities. Our findings revealed that, although urban and tourism development tend to limit the local amenities intended for residents, these are not necessarily perceived as incompatible with a residential living environment. In addition, residents adopt several strategies to satisfy their daily needs, but this behaviour contributes neither to the quality of the living environment, nor to a sense of place in the district. We propose to approach urban and tourism development in historic districts differently, by emphasizing the tensions and complementarities of uses rather than the incompatibility of functions.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical
Teacher disagreement score0.385
Threshold uncertainty score0.774

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.008
GPT teacher head0.223
Teacher spread0.215 · 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

Citations7
Published2018
Admission routes4
Has abstractyes

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