Finding Ways to Spain: migration experiences in the navigation of Beni Ensar-Melilla border
Bibliographic record
Abstract
Existing literature has examined transnational migration in the border zone of Beni Ensar (Morocco) and Melilla (Spain) from various perspectives. However, there is relatively little exploration of the experience of crossing this border. This article aims to address this gap by utilizing qualitative research conducted with migrants assisted by the Spanish Red Cross. The work employs a theoretical framework of migration trajectories and focuses on three types of border crossing experiences: by land, by sea, and as unaccompanied minors. The objective is to comprehend how participants describe the Beni Ensar-Melilla border area, the strategies they employ to navigate the border, and the significance of crossing it for them. I argue that, firstly, in order to navigate this challenging borderland, participants needed to cooperate with other migrants and demonstrate persistence. Additionally, unaccompanied minors relied on specific laws and reception conditions. Secondly, the act of migrating is linked to ideal plans in Europe that, if realized, have the potential to enhance the lives of participants and their families.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".