Mapping home: literary and filmic representations of multi-scalar dwelling
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.
Bibliographic record
Abstract
In this dissertation, I investigate the overlapping individual, relational, and social scales of home in contemporary literary and cinematic texts, drawing on Martin Heidegger’s writing on dwelling (as the essence of being human), Zygmunt Bauman’s concept of liquid modernity (particularly the commitment avoidance that its “fluidity” fosters), and Jacques Derrida’s work on hospitality (both the welcoming and hostile social practices that this term encompasses). I explore these ideas and scales of home in international and multi-medial texts, which include Mark Z. Danielewski’s House of Leaves (2000), Neil Gaiman’s Neverwhere (television series and novel 1996, graphic novel adaptation 2007), M. Night Shyamalan’s The Village (2004), Nicolas Dickner’s Nikolski (2005, trans. 2008), Lars von Trier’s Dogville (2003), and Wolfgang Becker’s Good Bye, Lenin! (2003). My corpus of texts demonstrates that a traditional understanding of home as a distinct location is incompatible with the realities of liquid modernity, and, moreover, sheds light on new modes of constructing home as a composite of locations and scales—a complex, multi-scalar, geocultural map of identity and belonging. Together, these texts show a dual pattern that makes visible the need to rethink the notion of home: an inclusive map of home on various scales helps home-makers to integrate the various places and people who populate their understanding of home, while the inability to conceive of home in this multifarious way nurtures social fissures, conceptual homelessness, and even psychoses. My main objectives are to challenge neutral, utilitarian conceptions of space, place, and home, and to demonstrate the possibility of what Heidegger calls “poetic dwelling” in liquid modern times and an increasingly inhospitable, market-driven social landscape
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it