Invisible Walls: Employment Struggles of Women with Limited Education in Albania
Bibliographic record
Abstract
The current study explores the employment struggles of women with limited education in Albania.They face challenges that affect their access to the labor market, considering how their employment opportunities are influenced by social, economic, and cultural factors.Key barriers included, but were not limited to, a scarcity of jobs, strong societal norms, financial constraints, and skills-labor market demand mismatch.The latter are confined to low-paid, insecure jobs without benefits or career development opportunities.This study also describes the important additional constraints placed by the patriarchal culture, responsibilities for care, and discrimination in reducing these women's possibilities for meaningful labor market participation.This is a qualitative research study, with interviews from diverse women, as the researchers provide a rich view of the struggle and resilience of the participants.These personal testimonies demonstrate how their challenges are a result of precariousness at work and financial difficulty to lack of access to career enhancement and support systems.The interviews reveal both similarities and differences of Albanian women as they experience employment challenges such as job insecurity and financial insecurity, educational limitations, societal norms and family responsibilities, limited access to professional development and support networks, unique experiences of discrimination and self-doubt.The findings suggest that is essential the need for targeted interventions in terms of expanding vocational training, flexible work arrangements, support for entrepreneurship, and inclusive employment policies.Such systemic barriers, identified in this paper, require deep changes in policies that transform women's economic functions, challenging broader social norms to greater equity and inclusion in the workforce in Albania.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".