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Record W4237189468 · doi:10.24124/2010/bpgub702

Planning for resilience: A case study of Kitimat, BC.

2010· dissertation· en· W4237189468 on OpenAlexaboutno aff
Jennifer Herkes

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
Fundersnot available
KeywordsCohesion (chemistry)Group cohesivenessResidenceFocus groupEthnic groupPsychological resilienceCommunity cohesionSociologySocial relationPublic relationsPsychologyPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

Kitimat, British Columbia was the first comprehensively planned town in the province. Built in 1954 to house the workers of Alcan, it was planned to be a town with strong social cohesion, a high quality of life, and resilient to change over time. The physical plan intended to encourage interaction while the social plan was meant to solidify those bonds, thereby developing social cohesion and community capacity supports for the town to potentially remain resilient. A triangulated research approach combines an historical analysis of Statistics Canada data, mapping techniques, as well as focus group and key informant interviews. Information obtained through the focus group and interviews is reviewed to understand the affects of the physical plan on the people and the community, and the data are further explored to determine what, if any, other factors influenced the development of social cohesion and resilience in Kitimat. With a better understanding of what encourages and prohibits interaction and the development of a sense of community, policies and plans can be developed to allow for the development of structures that encourage interaction and minimize those that inhibit it. The findings suggest that the physical organization of Kitimat encourages interaction and serves to support the development of social cohesion. Social cohesion is further developed through relationships based on factors such as ethnicity, job-type, length of residence, and interests. --P. ii.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.141
GPT teacher head0.562
Teacher spread0.421 · 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.

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

Citations1
Published2010
Admission routes1
Has abstractyes

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