An organizational analysis of road traffic crash prevention to explain the difficulties of a national program in a low income country
Bibliographic record
Abstract
BACKGROUND: Road traffic crashes (RTC), that daily kill 3400 people and leave 15,000 with a permanent disability could be prevented through the implementation of safety programs developed in partnership with governments and institutions. The relationship between key stakeholders can be a crucial determinant to the effectiveness of road safety programs. This issue has rarely been addressed. We conducted a detailed organizational analysis of the stakeholders involved in road safety programs in Lao People's Democratic Republic (Lao PDR). METHODS: A case study was performed. The framework used was a snowball effect in which the characterization of all key stakeholders and the links between them, as well as the factors that led to these links, were determined. The effect of the relations between key stakeholders on the prevention of RTC was assessed through an analysis of the transactional, intangible and controlling factors that influence these relationships. RESULTS: The design and implementation of road safety programs in Lao PDR suffer from weak relationships between stakeholders and a poorly functional bicephal leadership between the Ministry of Public Works and Transport and the non-governmental organisation called Handicap International. This poor coordination between key stakeholders is evident, particularly in the area of collective action and is reinforced by a lack of interest from several different stakeholders. Most agencies do not prioritize road safety. Uneven distribution of funding is another contributing factor. Strengthening the leadership is crucial to the success of the program. Some organisations have skills, power the decision making and the allocation of resources in regards to road safety programs. Encouraging participation of these organizations through a more prominent position would thus result in a better collaboration. Non-monetary rewards would further help to strengthen collaborative work. CONCLUSION: The bicephal nature of the leadership of road safety programs proves detrimental, is associated with a weak coalition between stakeholders, and contributes to the declaimed poor effectiveness of the existing programs. The study has identified non-monetary and realistic means of strengthening the collaboration between key stakeholders. Stakeholders need to revise their interpretive schemes, in order to actively support the reinforcement of government leadership of road safety policies.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".