Fashioning Identity: A Technocultural Analysis of Igbo Women Designers’ Self-Presentation on Instagram
Bibliographic record
Abstract
Using African Technocultural Feminist Theory (ATFT), this study explored how Nigerian Igbo women fashion designers use Instagram to perform digital identities. While there is extensive literature on self-presentation on social media, there is limited research on African women’s self-presentation from a feminist perspective. The Critical Technocultural Discourse Analysis (CTDA) of Instagram posts and interview data revealed that Instagram’s photo affordances allowed designers to showcase their intricate designs and facilitate the cultural digitization of Igbo-centric fashion. The result of the three-phased analysis revealed Nigerian Igbo women fashion designers employed visual aesthetics and authenticity in their entrepreneurial online presentation. The study also highlighted the reemergence of Nsibidi , a long-lost ideography within Igbo culture, facilitated by Instagram. In addition, the study revealed that Nigerian Igbo women fashion designers use Instagram to challenge societal norms related to femininity and womanhood. This study addresses the need to examine African women’s digital identities through a feminist lens, considering the impact of overlapping power structures on their self-representational choices on social media.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".