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Record W7115823178

Turning Belief into Action: The Role of Relationships, Trust and Leadership in Building Shared Belief and Motivating Organizational Support: A Case Study of an Anonymous Post-Secondary Institution in Ontario

2014· dissertation· W7115823178 on OpenAlexaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2014
Typedissertation
Language
FieldSocial Sciences
TopicPublic Relations and Crisis Communication
Canadian institutionsnot available
Fundersnot available
KeywordsInstitutionRelevance (law)StorytellingOrganizational cultureCreating shared valueTest (biology)Organizational communicationCode (set theory)
DOInot available

Abstract

fetched live from OpenAlex

This case study tests a new model for corporate communications called Building Belief, which urges a firm to constantly live up to its stated character and values so as to motivate its stakeholders to identify with it, support it, and promote it. The model was applied to a postsecondary institution in Ontario. Building on published theories and best practices related to culture, reputation, trust, relationship management, communications, employee engagement, strategy, leadership, storytelling, and social media, this study asked employees (faculty and staff), advisory committee members and leaders to define their organization’s culture and rate the extent to which the organization shares their values. This study finds that the organization’s stakeholders do have the potential to act as ambassadors, but just as in the private sector, a sense of shared belief is needed first. The study recommends the use of storytelling to build shared identity. It further suggests the involvement of the institution’s stakeholders in the cocreation of a culture code and the use of ongoing, two-way communications to deepen levels of engagement and strengthen people’s relationships with the institution. The Building Belief model was found to have relevance in the post-secondary sector. Finally, this study delivers a new tool to help any organization, public or private, quickly assess its level of shared values and connection with its stakeholders and gain insight into the dimensions that might need further attention to help build shared belief and turn it into action.

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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.647
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
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 head0.050
GPT teacher head0.256
Teacher spread0.206 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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