MétaCan
Menu
Back to cohort
Record W3115555762

Uwaridi kwani? (‘Why ‘Uwaridi’?’) Digital Literary Networks and the App-Propriation of Swahili Popular Novels

2020· article· en· W3115555762 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePostcolonial text · 2020
Typearticle
Languageen
FieldComputer Science
TopicICT in Developing Communities
Canadian institutionsnot available
Fundersnot available
KeywordsSwahiliPublishingNarrativeNewspaperDigital mediaLiteratureHistoryMedia studiesArtWorld Wide WebSociologyComputer scienceLinguistics
DOInot available

Abstract

fetched live from OpenAlex

This paper examines the current dynamics of publishing Swahili novels in digital media. In August 2016, a collective of writers formed the literary association “Umoja wa Waandishi wa Riwaya wenye Dira” (Union of Novelists with a Compass/Target”), Uwaridi, which in March 2017 launched a homonymous smartphone app for popular fiction. Based on several conversations with Hussein Tuwa, writer and co-founder of Uwaridi, I explore the double nature of this new digital literary network: A network of writers and their texts gone digital. A neat mobile phone network connection tends to replace not only the book shop or newspaper stall, but even the social media experience. Will the recent innovations in digital publishing outstage printed books of Swahili literature in Tanzania? Is this new ‘app-propriation’ likely to extend its networks towards Kenya, and further abroad? What are the main opportunities and challenges for writers and readers of Swahili fiction?

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.726
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.014
GPT teacher head0.213
Teacher spread0.199 · 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