Cartographies of Nation Building: Creating and Contesting the Egyptian Geo-body
Bibliographic record
Abstract
Both newly independent and well-established nation-states engage in varied nation-building activities and discourses in order to create some semblance of a coherent national identity and unity. Cartography is one of the major practices in nation building, playing a formative role in creating, sustaining, and at times even contesting the existence and legitimacy of nation-states. In this paper, I examine how the Egyptian “geo-body,” or the national territory, was constructed through different cartographic projects since its official, though nominal, independence in 1922. Drawing on a wide variety of maps published in Egypt since 1922, I focus on the official national cartographic discourses of the Egyptian state, as well as counter-cartographies that come from both the state and marginalized groups in Egypt. In doing so, I highlight how supranational and local scales are invoked with the national. As many scholars of critical geopolitics have asserted, it is essential to move away from the scale of the sta...
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.009 | 0.030 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".