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Record W7064218909

Art or Con? Exploring Instapoetry at the Nexus of Influencer Culture, Author-Entrepreneurism, and Literary Innovation

2024· article· en· W7064218909 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicX-ray Spectroscopy and Fluorescence Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsNexus (standard)PoetryPraiseLiterary criticismSituatedEmbodied cognitionOrder (exchange)LiterarinessSocial criticismPopular culture
DOInot available

Abstract

fetched live from OpenAlex

This dissertation examines what it means to be a poet originating from social media, commercially driven spaces of digital culture and commerce, and the nexus of influencer culture and entrepreneurism that impacts contemporary literary production online. Situated at the intersection of Canadian literary studies, media studies, and cultural studies, my dissertation conducts case studies of three “instapoets” in Canada: Tenille Campbell, Rupi Kaur, and Najwa Zebian. In the mid-2010s, a type of born-digital poetry known as “instapoetry” exploded onto the literary scene via social media. Following the publication of Kaur’s Milk and Honey in 2014, which sold over six million copies, print poetry sales rose to record-breaking highs. Instapoetry combines textual, visual, and paratextual, forms, as well as personal, sartorial, and embodied elements in both print and digital formats. Instapoetry’s success triggered widespread debates about instapoetry’s literariness along sharply divided lines. Whereas some critics praise it as a type of poetic innovation, others denounce its failure to meet the standards of traditional poetry. Like instapoetry, this dissertation is a combination: it crosses disciplinary schools of thought and modes of analysis. It seeks to understand the extent to which instapoetry intersects with, on the one hand, established literary traditions, institutions, or histories, and, on the other, with the nested entrepreneurial and commercial interests of social media platforms. As such, it is structured from most to least “literary”—not in an evaluative sense, but rather clinically—in order to theorize how social media impacts the purposes to which poetry is put today; figures the author into a new type of media celebrity; and creates new spaces of literary community. Each case study analyzes primary textual material such as print poetry collections; social media content like images, captions, and comments; and popular interviews in literary magazines, journals, and podcasts. Chapter One focuses on Tenille Campbell. The poet, who is Dene and Métis, has appropriated the algorithm-controlled network of Instagram to write herself into an evolving Indigenous literary tradition and community of artists, writers, and entrepreneurs, bypassing the politics of Canadian publishing and defining herself as an Indigenous author. Chapter Two examines Rupi Kaur, who occupies a liminal position between traditional literary institutions and social media influence. A paraliterary figure, she straddles two territories, first, as a self-branded social media persona, and second, as a Canadian literary brand. This liminality breeds a sense of uneasiness within the Canadian literary scene, as it challenges the power and prestige of the literary establishment. Chapter Three looks at how poetry functions as primarily entrepreneurial material when it is specifically mobilized as self-care content, rendering a national framework irrelevant entirely. This poetry, while it appears “literary,” is valued not for its aesthetic purposes, but for its perceived ability to transform readers into better, happier, healed individuals. Instapoetry in Canada ultimately connects to larger transformations in the contemporary literary sphere as new and old ecosystems collide. The “instapoetry” label merely scratches the surface of a multi-platform, multi-media, and transnational phenomenon.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.082
Threshold uncertainty score0.740

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.090
GPT teacher head0.328
Teacher spread0.238 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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