MétaCan
Menu
Back to cohort
Record W4415587042 · doi:10.21083/crrf.v27i1.8584

Four stories of Summerside’s cultural resilience

2025· article· W4415587042 on OpenAlexaffabout
Lori Ellis, Paula Kenny

Bibliographic record

VenueProceedings of the Canadian Rural Revitalization Foundation · 2025
Typearticle
Language
FieldNursing
TopicNursing Education, Practice, and Leadership
Canadian institutionsWind Energy Institute of Canada
Fundersnot available
KeywordsGovernment (linguistics)Resilience (materials science)Community resilienceThe artsCultural heritageGeneral partnershipEconomic base analysisPsychological resilience

Abstract

fetched live from OpenAlex

Summerside's modern support of Arts and Heritage dates back 45 years to modest beginnings. Summerside is no stranger to community resilience. Summerside bounced back from a shipbuilding centre to become an Island transportation terminus, followed by a world leading silver black fox production and export centre and finally the home of a military base for 50 years. 1989 was a pivotal year - the Canadian Forces Base Summerside would be no more. The citizens of this town spoke as one fighting to retain it, without success. A Federal government Tax Centre would be its replacement, itself an extraordinary feat as not every former military town would receive that level of investment by the Federal government. Cultural initiatives helped sustain the community. Summerside Bounces Back is a panel presentation on the role of resilience told by four different cultural players. Two are very successful community based non-government cultural initiatives and two are equally successful government (one provincial, one municipal) initiatives that enjoy a high level of community connectedness. You will feel you know Summerside when you meet the players who will share why and how community resilience played a part in their successful establishment. Which came first, the resilience or the culture?

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.311
Teacher spread0.284 · 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 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
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Canadian Rural Revitalization FoundationSame topicNursing Education, Practice, and LeadershipFrench-language works237,207