Expanding the shield and facing the challenges: integration of women in Botswana Defense Force
Bibliographic record
Abstract
Botswana remains one of the few countries in the world (and the only country in the South African Development Community (SADC)) where females are legally prohibited from joining the military. The political and social pressure in the 21st century has softened the opposition of many influential politicians and bureaucrats to calls for inclusionary statutes. This thesis examines the possibility of opening doors to women in the Botswana Defence Force (BDF). It examines the policies, programs and scope of the role of women in the US armed services, Canadian Forces (CF) and the South African National Defence Forces (SANDF). It identifies from these highlights the most effective approaches to recruiting, training, and retaining women in the BDF once the opportunity is availed. In particular, this thesis examines the Six critical policies of the US armed services and the CF, namely, sexual harassment, fraternization, employment of women, equal opportunity, pregnancy, and family care. This thesis considers the lessons from these for the BDF. Two critical cases of sexual harassment, (the 1991 Tailhook Navy and Marine Corps Convention and the 1996 US Army's Aberdeen Proving Ground incident), are highlighted in the study. The leading recommendations emphasize the need for the BDF to take the steps required to evoke a cultural change to affect the attitudes and perceptions of personnel and to examine how the SANDF administers its policies as they pertain to women.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".