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Record W2337997476 · doi:10.14288/1.0075673

‘Recent trends in community programming : an assessment of Lynn Canyon Ecology Centre’

2014· article· en· W2337997476 on OpenAlexaboutno aff
Eric R. Eaton

Bibliographic record

VenuecIRcle (University of British Columbia) · 2014
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
Fundersnot available
KeywordsCanyonEcologyGeographyCommunityBiologyCartographyHabitat

Abstract

fetched live from OpenAlex

Due to a decline Vancouver’s social capital from an aging population and increasing time spent indoors the Lynn Canyon Ecology Centre should take note of the following recommendations: continue to focus on differentiating the content of programming; keep up with new marketing strategies (increase internet presence); rebrand programming as having physical exercise involved; engage high-school students by encouraging the creation of after school volunteer programs, and enable them to organize and design the programs. These recommendations were designed for the Lynn Canyon Ecology Centre, in order to capitalize on potential opportunities, and fill in current program gaps. The recommendations were created in conjunction with an informed assessment of relevant demographic and social trends of the past decade in the District Municipality of North Vancouver, British Columbia. All of the above recommendations and conclusions were found in pursuit of answering the following two research questions: 1) What are the driving factors causing changes in community program participation from families in North Vancouver, and is this consistent with Metro Vancouver? 2) What can the Lynn Canyon Ecology Centre do in terms of programming to foster community support and involvement? Supporting arguments provided are derived from primary and secondary source research, which includes peer-reviewed literature regarding environmental education, marketing strategies, demographic statistics and the health affects of physical activities; and four in-depth interviews with public programming staff at various organizations in Metro Vancouver.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.602
Threshold uncertainty score0.803

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.036
GPT teacher head0.340
Teacher spread0.304 · 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 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

Citations0
Published2014
Admission routes1
Has abstractyes

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