Att bo i Södertälje och studera på sfi : Sex irakiska flyktingars syn på sina sfi-studier, staden de bor i och att vara flykting med en framtid i Sverige
Bibliographic record
Abstract
It is widely recognized that the town of Södertälje, a small Swedish town of 85 000 inhabitants, has alone received more war refugees from Iraq than the US and Canada have put together. Whilst writing this thesis had nearly 6000 Iraqi refugees sought their way to Södertälje since the US invasion in Iraq 2003. Nevertheless, life is not what the media and the government retail. Six of these Iraqi refugees who resided in Södertälje share their life stories in the following thesis. They discuss their escape from Iraq and the difficulties of living in the segregated parts of Södertälje where they solely speak Arabic and Assyrian, whilst learning Swedish at sfi (Svenska för invandrare, Swedish for immigrants). Another distress is related to the unsecure future in Sweden waiting ahead. The aim of this thesis is to engage in, and highlight the studies of six sfi-students in their endeavor to learn Swedish, whilst struggling through Swedish bureaucracy and experiencing despair due to their situation and uncertain future.
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 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".