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Record W3088069362 · doi:10.1177/0276146720956380

“For the Gram”: An Exploration of the Conflict between Influencers and Citizen-Consumers in the Public Lands Marketing System

2020· article· en· W3088069362 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Macromarketing · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsBrock University
Fundersnot available
KeywordsSocial mediaGratificationMarketingInfluencer marketingBusinessTourismRecreationPublic relationsAdvertisingPolitical scienceMarketing managementRelationship marketingPsychology

Abstract

fetched live from OpenAlex

Capturing memories is integral to public lands visitors’ consumer experiences. Today, social media allows us to share photographs and videos in the public domain, whether it be for instant gratification, economic gain, or both. The phenomenon of sharing public lands digital imagery on social media has created tensions in the public lands marketing system (PLMS) between those wanting to preserve the outdoors and those seeking to monetize it. Using the Instagram account @publiclandshateyou as a case study site, this research utilizes an interpretive “thick data” visual analysis to examine how interlinked marketing systems (e.g., travel, tourism, outdoor recreation), which includes the social media marketing system (SMMS) contribute to this conflict in the PLMS. Findings indicate that citizen-consumer oriented practices, rooted in “sense of place,” attempt to bring change to the interlinked marketing systems.

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.

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)0.019
metaresearch head score (Gemma)0.007
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 score0.508
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.136
GPT teacher head0.360
Teacher spread0.224 · 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