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Record W2107941751 · doi:10.22230/cjc.2005v30n2a1463

Community Engagement, Performance Measurement, and Sustainability: Experiences from Canadian Community-Based Networks

2005· article· en· W2107941751 on OpenAlexaffvenueabout
Ricardo Ramı́rez

Bibliographic record

VenueCanadian Journal of Communication · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSustainabilityTypologySocial capitalKnowledge managementProcess (computing)Public relationsICTSCommunity engagementSociologyBusinessPolitical scienceInformation and Communications TechnologySocial scienceComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Community-based networks (CBNs) are local organizations that have introduced information and communication technologies (ICTs) as tools for social, economic, and cultural development. This study reports on the achievements of 11 Canadian CBNs in terms of how they engage their clients and how they address sustainability. A tentative typology is provided and contextualized with the literature on social capital. Community engagement was reported to be an ongoing process, involving a broad range of community stakeholders and leading to a responsive project management style. The track record with sustainability shows a growing recognition about the importance of base-line data, an awareness about the challenge in defining what to measure, and the realization that performance measurement is neither easy nor inexpensive.

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)0.005
metaresearch head score (Gemma)0.013
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.434

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0310.008
Scholarly communication0.0050.002
Open science0.0020.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.074
GPT teacher head0.290
Teacher spread0.216 · 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

Citations15
Published2005
Admission routes3
Has abstractyes

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