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Record W7115813093

Public relations, marketing and fundraising in Canadian nonprofits: Who is better at relationship?

2016· dissertation· W7115813093 on OpenAlexaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2016
Typedissertation
Language
FieldSocial Sciences
TopicPublic Relations and Crisis Communication
Canadian institutionsnot available
Fundersnot available
KeywordsControl (management)Quality (philosophy)Function (biology)SustainabilityNonprofit organizationKey (lock)Survey data collection
DOInot available

Abstract

fetched live from OpenAlex

The nonprofit landscape in Canada is extremely competitive and organizations looking to be successful for the long term will need the ability to build effective relationships with their key audiences. Over the last 30 years, the quality of organizational-public relationships (OPR) has been measured by a number of public relations scholars but it was Hon and Grunig (1999) who identified a number of indicators, including trust, commitment and control mutuality. Furthermore, scholarly literature shows there is also the potential for encroachment of public relations by other functions such as fundraising and marketing, as financial sustainability remains a great concern for nonprofits. This study examines public relations, marketing and fundraising structures in the human services nonprofit subsector in Canada against OPR indicators to explore whether there is a relationship between structure and engagement effectiveness. The researcher deployed a nationwide survey reaching 115 public relations, marketing and fundraising professionals, conducted in-depth interviews with 11 CEOs and senior leaders of nonprofit organizations and analyzed six of their corresponding organization charts in a content analysis. The research shows that generally the organizations in this subsector enjoy high levels of trust and commitment from their audiences, but control mutuality is an area of weakness. The researcher also found that encroachment of the public relations function was not occurring to a great extent. This study raises possibilities for future research of OPRs and other nonprofit subsectors as well as research that examines the relationship between organizational size and engagement effectiveness.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.660
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0040.000
Scholarly communication0.0010.003
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0950.000

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 head0.029
GPT teacher head0.249
Teacher spread0.220 · 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
GenreOther

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 routes1
Has abstractyes

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