MétaCan
Menu
Back to cohort
Record W2289448264 · doi:10.18192/clg-cgl.v5i1-2.1466

Neighbourhood Cultural Mapping: Lessons Learned from a Pilot Project in Bayshore

2015· article· en· W2289448264 on OpenAlexvenueaboutno aff
Ben Dick

Bibliographic record

VenueCulture and Local Governance · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsNeighbourhood (mathematics)GeographyImmigrationDiversity (politics)SociologyCultural diversityHumanitiesAnthropologyArtArchaeology

Abstract

fetched live from OpenAlex

The cultural mapping project in Bayshore was the first of three neighbourhood cultural mapping pilot projects in Ottawa. City-wide cultural mapping in Ottawa had shown Bayshore to have few cultural resources, and socio-economic indicators had shown Bayshore to be a low-income neighbourhood that faced many problems. However, discussions with neighbourhood residents told a different story. Bayshore has many cultural resources, though they are often intangible. Its residents benefit from the neighbourhood’s cultural diversity, as it is one of the most diverse neighbourhoods in the city. Informal networks have been established in Bayshore that provide support to new immigrants, and a wide variety of specialty stores and restaurants have been established nearby to serve this diverse community. The neighbourhood’s diversity may also be supporting the development of a creative cluster nearby. The Bayshore project forced the City’s cultural mapping team to re-think the way culture is defined and categorized.Keywords: neighbourhood cultural mapping, intangible cultural assets, informal networks, cultural diversity, creative clusterRésumé: Le projet de Bayshore est le premier de trois projets pilotes de cartographie culturelle initiés à la ville d’Ottawa. Une cartographie culturelle à l’échelle de la ville a révélé que le quartier de Bayshore était moins doté au plan de ressources culturelles que d’autres quartiers de la ville. De plus, les indicateurs révèlent que le quartier en question est également un quartier à faible revenu qui est confronté à plusieurs problématiques sociales et économiques. Cependant, des entretiens auprès des résidents du quartier nous offrent une autre perspective. Ces entretiens révèlent notamment que les ressources culturelles de Bayshore sont sous-estimées puisqu’elles sont souvent intangibles. Il est révélé que les résidents du quartier tirent profit de la diversité du quartier le plus culturellement diversifié de la ville. Bayshore se caractérise par une diversité de réseaux sociaux informels et par une grande diversité de commerces et de restaurants. Cette grande diversité serait un facteur qui participerait au développement d’une grappe créative dans un quartier voisin. Cet article met en évidence plusieurs constats qui nous invitent à revoir et repenser comment la culture est construite et modélisée dans le cadre des projets de cartographie culturelle.Mots clé: cartographie culturelle d’un voisinage, ressources culturelles immatérielles, réseaux informels, diversité culturelle, groupement créatif

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)0.021
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.852
Threshold uncertainty score0.294

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0150.006
Scholarly communication0.0060.006
Open science0.0050.009
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.191
GPT teacher head0.343
Teacher spread0.152 · 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 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

Citations2
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueCulture and Local GovernanceSame topicCultural Industries and Urban DevelopmentFrench-language works237,207