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Record W3165798067 · doi:10.5325/jafrideve.21.1.0014

The Nexus between Instagram and Digital Entrepreneurship

2020· article· en· W3165798067 on OpenAlexaff
Bamidele Adekunle, Christine Kajumba

Bibliographic record

VenueJournal of African Development · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsUniversity of GuelphToronto Metropolitan University
Fundersnot available
KeywordsSocial mediaEntrepreneurshipDisadvantagedPremiseNexus (standard)MarketingSocioeconomic statusPublic relationsBusinessAdvertisingSociologyPolitical scienceWorld Wide WebEconomicsComputer scienceEconomic growth

Abstract

fetched live from OpenAlex

ABSTRACT Social media platforms have transformed entrepreneurial activities. These social platforms are used for communication and marketing, connecting current and prospective customers to service providers, and connecting and engaging marketers to end users. Instagram is one of the fastest growing and most popular social platforms for socialization, personal indulgence, and information and product sharing. Based on this premise, it is important to understand the role that Instagram plays in digital entrepreneurship. In order to have a better understanding of the socioeconomic implications of the use of social media, this article analyzed secondary and primary data, direct and participant observations, and inductive reasoning. It presents Instagram's visual power and high number of followers, which enhance sales and attract a new set of entrepreneurs who would otherwise be disadvantaged as a result of cultural, economic, and political barriers.

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)0.001
metaresearch head score (Gemma)0.007
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.005
Scholarly communication0.0040.003
Open science0.0000.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.032
GPT teacher head0.262
Teacher spread0.230 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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