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Record W1532821382 · doi:10.15353/joci.v3i1.2389

Community Organizations in the Information Age: A study of community intermediaries in Canada

2007· article· en· W1532821382 on OpenAlexfundvenueaboutno aff
Prof. Vanda Rideout, Andrew Reddick, Susan O’Donnell, William J. McIver, Sandy Kitchen, Mary Milliken

Bibliographic record

VenueThe Journal of Community Informatics · 2007
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
FundersHuman Resources and Skills Development CanadaHealth Canada
KeywordsIntermediaryCommunity organizationPublic relationsGovernment (linguistics)BusinessCensusFocus groupLibrary scienceSociologyPolitical scienceMarketing

Abstract

fetched live from OpenAlex

The aim of the Community Intermediaries Research Project (CIRP) was to investigate the social challenges and needs addressed by Canadian non-profit community-based organizations, the social and community contexts in which they operate, and the information and services they provide to citizens. These organizations are “community intermediaries” because they act as links between the various levels of government (federal, provincial, and municipal) and citizens, providing social services and information to their clients and communities.The CIRP research team used a case-study, mixed methods approach. In-depth case studies of four types of community organizations in different parts of Canada were performed. These employed: onsite observations; in-depth interviews with managerial and staff members; focus group discussions with staff (paid staff and volunteers) and with clients; and self-directed surveys with the organization’s staff, volunteers and clients. Quantitative analysis produced in-depth community profiles using secondary Statistics Canada census data. Data were also gathered from the various forms of content generated by the organizations to deliver the services and information they provide to their respective clients (web pages, pamphlets, newsletters, etc.).This is an invited re-publication of the CIRP final report .

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)0.037
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.316
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0370.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0040.000
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0000.013
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 head0.065
GPT teacher head0.393
Teacher spread0.328 · 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

Citations2
Published2007
Admission routes3
Has abstractyes

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