Scattering journeys, regenerative environments. A material ecocritical reading of the diasporic storyworld in Shaun Tan’s refugee graphic novel The Arrival
Bibliographic record
Abstract
Pushed out of time, place, and history, refugees are typically imagined as humanitarian subjects whose lives are marked by exclusion and constitutive otherness. Thought of as objects of pity, but also as disrupters of an established order, forcibly displaced people are imprinted by a logic of compassion, passivity, and aberration. Literature, however, provides an alternative site for the representation of refugeedom as an empowering experience that enables the formulation of a different sense of self as well as creative human-environmental interactions. This article will focus on the locations where such interactions take place by examining the foreign cityscape in Shaun Tan’s refugee graphic novel The Arrival (2006). Unlike traditional representations of the new land as a place of loss, dispersal, and powerlessness, Tan’s illustrations portray the host city as both a tangible and imagined space of diversity, where inter- and intra-specific interactions play a crucial role in the protagonist’s physical and personal journey. Through a material ecocritical lens, the article examines how the matter of the book, both living and non-living, tells a story of successful adaptation and home building thanks to the protagonist’s capacity to establish a sense of intimacy with the nonhuman world that surrounds him. In conclusion, the apparently unhomely city portrayed by Tan is ultimately the setting of an alter-tale, that is, an alternative narrative in which the interrelationship between the refugee and the material entities that inhabit the land of arrival opens up unexpected possibilities for the displaced to experience not much the scattering as the regenerative potential of refugeedom.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".