Perception of Lebanese middle school students about engineering
Bibliographic record
Abstract
In a male-dominated Middle Eastern society, female academics and professionals have come a long way in recent decades, challenging long-held stereotypes about women holding careers in fields of science and technology. Despite these gains, however, female enrollment in Lebanese engineering programs remains low-less than a quarter of all engineering students, according to a recent study. The current research, at the Lebanese American University (LAU), assesses the reasons that are possibly discouraging female students from pursuing engineering careers while targeting to make a step towards improving female representation. Encouraging female students to pursue careers in engineering requires an understanding of what young female students already know about the field, as well as recognizing what might spur their interest in choosing engineering professions over the more traditionally female-populated fields of literature and humanities. As a first step, a school survey was conducted to investigate and assess the current knowledge of female middle school students about engineering, with special emphasis on civil engineering. The main focus of the school survey was to identify the level of awareness of career alternatives, gender-related restrictions, parental guidance, social factors, and cultural factors that might affect the career choice. This paper summarizes the results of the survey and analyses the main factors that may help in encouraging women to join engineering schools.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".