Translating the nation through the sustainable, liveable city: The role of social media intermediaries in immigrant integration in Copenhagen
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
This article explores settled Western migrants whose digital content provides recent, mostly Western migrants in Copenhagen with local know-how and city-related information. This new type of informal integration intermediary functions as an emerging digital component of wider urban integration industries that assist migrants with settlement and social integration. We draw on the sociological theory of translation as a social, productive practice that constructs new meanings through selective interpretations and conceptualise the work of these bloggers as translation. Relying on the analysis of their blog and Instagram posts, and on interviews, this article shows how their translations of the city, and through it Danishness, play a critical role in mediating narratives of ‘becoming local’. Despite the differences between the bloggers’ respective translations (including those afforded through blogs vs Instagram) and despite criticism of a lack of inclusion of the socio-cultural differences in Denmark, these intermediaries ultimately reinforce for newcomers the expectations of the ‘green-city citizen’ and integration into Danish culture and lifestyle. We argue that what makes their translations resonate is not only that social media itself allows them to perform their having become (almost) local, but also that they carefully use their personal reflections as migrants. At the same time, the fact that their personal experiences of the city have been shaped by their positionality as white migrants feeling very welcomed, and even passing for locals, in the city curtails these bloggers’ wider potential as informal intermediaries filling a gap within Copenhagen’s urban integration industries.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it