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Record W4403237236 · doi:10.11114/smc.v12i4.7111

The Actualities of Public Relations Practice at an Eastern Ontario University: A Quasi-ethnographic Study

2024· article· en· W4403237236 on OpenAlexaboutno aff
Mohammed El-Astal

Bibliographic record

VenueStudies in Media and Communication · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Relations and Crisis Communication
Canadian institutionsnot available
Fundersnot available
KeywordsEthnographySociologyMedia studiesPolitical scienceAnthropology

Abstract

fetched live from OpenAlex

Although various studies have used ethnographic techniques to examine different concepts, contexts, and practices in public relations (Sriramesh, 2000; Daymon & Hodges, 2009), none of these studies ethnographically examined the culture within which public relations is practiced, and discourse is produced in a college or university context. This quasi-ethnographic study aims to: (1) produce an account of the core aspects of the culture within which public relations is practiced at a university in Eastern Ontario and (2) identify what PR model best represents the PR practice there. To collect data for this study, I conducted e-mail interviews with five public relations participants at the university under investigation to collect data for this study. The data collected was about the groups’ routines, practices, and behaviors that shape their experience and facilitate producing relevant discourse. I also collected some genres and documents. The findings showed that (1) collaboration characterized the culture within which PR performs its duties and activities and produces relevant discourse, and (2) the two-way asymmetrical model best represents the PR practice in the university examined. Besides filling the gap identified here, the study contributes to theory and practice in the field. It benefits those who teach public relations writing and the institution itself as it evaluates how excellent the PR practice in that institution is.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.658
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.144
GPT teacher head0.401
Teacher spread0.257 · 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
Published2024
Admission routes1
Has abstractyes

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