Contextual phases in the institutionalization of the environmental assessment of road development in Cameroon
Bibliographic record
Abstract
The aim of this paper is to demonstrate that the institutionalization of the environmental assessment (EA) of road development in Cameroon is context-sensitive. A content analysis of literature and key stakeholders' interviews reveals that socio-economic processes of the 1990s guided by, among others, the concepts of sustainable development, poverty reduction and good governance shaped the context of forestry and environmental policy reforms that led to the institutionalization of EA of road development. The Rio Earth Summit, the involvement of donors and non-governmental organizations in release mechanism programmes and projects enhanced this process. With this background, three phases were determined: the marginality phase (before 1992), when roads were constructed without EA, a general formalization phase (1992–1994), during which a nationwide EA framework was promulgated, and a specialization phase (after 1996), when the implementation of EA of road development became operational, even before the nationwide system. An understanding of the context must be included in the institutionalization process of EA, especially in developing countries.
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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 | 0.017 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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 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".