Walls all around: barriers women professionals face in high-tech careers in Bangladesh
Bibliographic record
Abstract
Purpose The purpose of this paper is to create a nuanced understanding of the barriers women high-tech professionals face in Bangladesh. The main aim is to identify the extent to which these barriers are common across different contexts and to explore the barriers that are unique and situated in the local socio-cultural context. Design/methodology/approach In-depth interviews with high-tech professionals were conducted to identify and explore the barriers. Findings Although some of the barriers are common across different contexts, most of the barriers women professionals face arise due to the interaction between situated socio-cultural practices and gender. The dynamics of socio-cultural and patriarchal norms reinforce gender biases and gendered practices that afford men with greater control over resources and systematically limit women’s access to opportunities. Research limitations/implications The study recruited 35 participants using snowball sampling. From a methodological perspective, future research could benefit from recruiting a larger, more varied sample using random sampling. Practical implications Women experience barriers due to both internal organizational features and external contextual barriers. The findings suggest that some of these barriers can be removed through governmental and organizational policies and through appropriate intervention strategies delivered in partnership with governmental and non-governmental organizations. Originality/value The study makes a unique contribution by using a macro-social lens to analyze the meso-organizational practices and micro-individual phenomena thereby providing a holistic view of the barriers faced by women professionals in Bangladesh.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.000 | 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 teacher head, 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".