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Record W4290630586 · doi:10.25139/jsk.v6i2.4870

Digital marketing communication for archery sports equipment on Instagram @vienetharcheryofficial

2022· article· en· W4290630586 on OpenAlexaff
Teguh Dwi Putranto, Ephraim Theodore S. Vallejo

Bibliographic record

VenueJurnal Studi Komunikasi (Indonesian Journal of Communications Studies) · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsUniversity of Alberta
FundersUniversitas Multimedia Nusantara
KeywordsPublicityAdvertisingSports marketingMarketing communicationBusinesssports equipmentMarketingEngineeringMarketing managementRelationship marketing

Abstract

fetched live from OpenAlex

The sports equipment business is one of the businesses that is currently starting to develop. Supported by the desire of the community to engage in sports, one of which is archery, Vieneth Archery Official, one of the archery equipment shops, takes advantage of this situation. The purpose of this study was to digitally determine the marketing communication of archery sports equipment on Instagram @vienetharcheryofficial. The method used in this research is Krippendorff content analysis which is carried out by collecting data on the Instagram account @vienetharcheryofficial from 1 May 2022 to 30 May 2022. The conclusion of this study shows that Vieneth Archery, as an archery equipment shop, carries out digital marketing communications through @vienetharcheryofficial Instagram posts dominated by public relations and publicity efforts.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.040
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0400.004

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 head0.083
GPT teacher head0.375
Teacher spread0.292 · 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 designObservational
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

Citations7
Published2022
Admission routes1
Has abstractyes

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