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Record W2561566937 · doi:10.15173/jpc.v5i1.2595

The new lobbyist rolodex: PR

2016· article· en· W2561566937 on OpenAlexaffvenueabout
Jennifer Thomlinson

Bibliographic record

VenueJournal of Professional Communication · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Relations and Crisis Communication
Canadian institutionsSpectra Energy (Canada)
Fundersnot available
KeywordsPublic relationsGovernment (linguistics)Social mediaPublic administrationPolitical sciencePosition (finance)SociologyBusinessLaw

Abstract

fetched live from OpenAlex

AbstractDespite its long history and key role in the development of public policy, serving the needs of virtually every sector of society, lobbying is an underdeveloped area of academic research. This study aims to establish an understanding of lobbying at the federal level in Canada and its synergies with communications and public relations. Through a review of existing scholarly research, as well as in-depth interviews with 15 federally-registered lobbyists, five senior communications executives, and a survey of GR practitioners, this paper reveals that lobbying is very much aligned with public relations, especially as the online and social media landscapes continue to grow and evolve. It concludes that integration between the two fields is necessary, if not inevitable, and that greater public relations, marketing and social media expertise should be leveraged to position the government relations practice for a future that embraces the new digital rules of engagement.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.602
Threshold uncertainty score0.800

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.008
Scholarly communication0.0090.003
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0180.002

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 head0.026
GPT teacher head0.378
Teacher spread0.352 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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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