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Record W2561469380 · doi:10.15173/mjc.v11i0.1410

An Examination of How World Vision Canada Communicates with Publics of Various Ideological Backgrounds and Moves Them to Donate

2016· article· en· W2561469380 on OpenAlexaffvenueabout
Julia Rim Shepard

Bibliographic record

VenueThe McMaster Journal of Communication · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Relations and Crisis Communication
Canadian institutionsMcMaster University
Fundersnot available
KeywordsIdeologyFaithDocumentationActive listeningContext (archaeology)PublicsPublic relationsSociologySalientContingencyIdentity (music)Political scienceMedia studiesEpistemologyLawAestheticsCommunicationHistory

Abstract

fetched live from OpenAlex

This case study explores how a charitable organization, World Vision Canada, engages publics of various ideological backgrounds and moves them to donate based on a number of contingency factors, as well as the community-building and co-creational theories of public relations. How the organization is identifying, communicating, listening, and responding to core audiences of various denominations and faith backgrounds was studied. Three salient points emerged from interviews, documentation, and archival records: First, the organization is able to identify and communicate with its broad base of core audiences, and it has been able to do so thus far by striking the right balance. Second, it has mechanisms in place that allow it to listen and engage with these audiences deeply and regularly. Finally, the organization needs to further articulate its Christian identity, to better communicate how development work is carried out in the context of its faith motivations, and to tailor communications uniquely for current and future audiences.

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)0.003
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 score0.845
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.032
GPT teacher head0.285
Teacher spread0.254 · 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
Published2016
Admission routes3
Has abstractyes

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