Epistolarity and Decolonial Aesthetics in Carola Grahn’s Look Who’s Talking (2016)
Bibliographic record
Abstract
This chapter explores how Sámi artist Carola Grahn's silent video, Look Who's Talking (2016), creatively intervenes in newer digital epistolary formats to recalibrate them for a decolonizing project. Specifically, I attend to how Grahn mobilizes ‘epistolarity’, to borrow Hamid Naficy's term, in ways that subvert colonial image histories, practices, and gazes. I also analyse the implications of how this epistolarity is, as Naficy argues, ‘produced under erasure’, in this case, the systemic erasure of Indigenous languages across the globe as mandated by state-sanctioned ‘educational’ institutions. To conclude, I consider the significance of Look Who's Talking 's exhibitionary context ( Among All These Tundras , 2018–2019) and, in particular, its dialogic relation to works by other Indigenous artists of the circumpolar north. Keywords: decolonial aesthetics; electronic epistolarity; video installation; Sámi culture; Hamid Naficy Métis artist David Garneau's painting, Aboriginal Curatorial Collective Meeting (2011), is composed of nine frames, each containing a series of speech bubbles resembling the kind one might encounter in a comic book or graphic novel. However, the words – and those presumably speaking them – are missing. For Garneau, this image ‘tries to picture irreconcilable spaces of Indigeneity without giving away any content’ and, in the process, attempts to ‘signal that something interesting is going on beyond the colonial gaze’. In other words, for Garneau, his painting is a resistance to the scopophilia that underpins a colonial drive, one also motivated by ‘an urge to penetrate, to traverse, to know, to translate, to own and exploit’. It is an act of ‘refusing translation and full explanation’, of preserving sites and spaces in which Indigenous peoples speak ‘with one's own and in one's own way’ beyond the scopic and representational regimes of white settler-colonizers. In Sámi artist Carola Grahn's silent video Look Who's Talking (2016, 3min 40sec, looped), the scopic and epistephilic regimes of white settler-colonizers are also thwarted. Apart from a few emojis, simple line drawings, black and white portraits of Game of Thrones (2011–2019) characters, and an animated celestial map, the work does not contain any images. Neither Indigenous bodies – including Grahn's – nor Sámi cultural practices or spiritual sites are subject to representation. There are no picturesque sites of Sápmi to aestheticize Grahn's words about her travels or give visual form to the reductive tropes historically associated with Sámi life.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".