Through the border : Senegalese gendered migration to Spain (2005-2010)
Bibliographic record
Abstract
This dissertation provides a geopolitical and gender analysis of the border that was built between 2005 and 2010 to stop unwanted migration from Senegal to Spain. I combine an investigation of institutional practices and of the experiences of migrants who crossed (or tried to cross) that border. This work constructs a genealogy of the Spanish - Senegalese border, including the obstacles placed to stop unwanted migration and the strategies adopted by migrants to enter EU space. To do so I draw from three bodies of literature: scholarship on migrant transnationalism, critical geopolitics, and feminist political geography. This analysis is built on extensive primary research complemented by secondary data, including life histories, participant observation, and interviews with migrants, members of their transnational social networks, former smugglers, service providers, supra-state organizations, state bureaucrats, and state security forces, as well as official statistics, legislation, and media accounts. I contend that gender is an articulating factor of international migrations. In the case of contemporary Senegalese migration to Spain, I argue that the re-enforcement and militarization of the border was disproportional to the number of migrants using land and sea routes. These efforts were partly responsible for a decrease in illegal migration by land and sea after 2007, but migration by air and secondary migration from other countries of the EU (which represent the majority of the migrant flow) was unaffected. Despite the obstacles placed to stop it, the migration of Senegalese continued and even increased during this period, mainly thanks to the support that transnational social networks provided to migrants. The main consequence of the preventive and defensive anti-immigration measures adopted was a re-territorialization of the EU border. The findings suggest the importance of integrating a variety of scales in the study of the processes, actors, and mechanisms involved in the territorial re-definition of state and supranational borders. In the case of the EU, I contend that as a response militarization is ethically questionable, economically wasteful, and inadequate. Finally, this study suggests the need to engage in a mobile cartography of the migrant transnational network to account for its transformations across time and space.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".