Returning to homeland: Sigur Ros' Heima and the cultural landscapes of Post-Rock
Bibliographic record
Abstract
The complex ways music sounds out space cannot be reduced to a mirror theory in which the contours of place are simply reflected in music's emotional architectures. Post-rock is a fruitful genre for problematising this notion, as its practitioners are motivated to sonorously re-construct, or at least mourn, the spatial erasures of late capitalism, epitomised by the apocalyptic melancholy of urban redevelopment represented in Canadian ensemble Godspeed You! Black Emperor. Icelandic quartet Sigur Rós maintain a skewed relationship to this primarily American genre, seeming instead to simply evoke the untouched natural beauty of their homeland, fulfilling discourses of Scandinavian 'purity' registered in the perennial critical descriptor for their sound: 'glacial'. Following the band's return to Iceland for a series of free concerts, the 2007 documentary Heima ostensibly affirms Western audiences' perception of their music as little more than the soundtrack to a 'Welcome to Iceland' tourism reel. Yet must things be read this way? This paper considers music's central role in constructing 'geographic knowledge' through a brief history of the affective cartography of post-rock, before critically reading the highly mediated forms - digital documentary, concert spectacle and recorded music - that constitute Sigur Rós' cultural landscape. I highlight the group's revival of the political project of post-rock through their accounting for capital's ecological refuse points, whilst paradoxically questioning their music as reflective of a 'natural' Iceland. Heima, that is, performs a conscious, if contradictory, audiovisual relationship to Iceland, one that is as much motivated by a conservative 'return home' as it is by a need to question one's homeland.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".