The context of REDD+ in the Democratic Republic of Congo: Drivers, agents and institutions
Bibliographic record
Abstract
Reviewing the conditions in which the Reduction of Emissions from Deforestation and Forest Degradation (REDD+) mechanism is being established in the Democratic Republic of Congo (DRC) is part of Component 1 of the Global Comparative Study on REDD+ (GCS-REDD) being conducted by the Center for International Forestry Research. The overall aim of this global study is to provide decision-makers, practitioners, donors and the scientific community with reliable information on the dynamics of national actions related to the REDD+ mechanism. Discussions on REDD originally seemed to focus on the construction of a global structure and the establishment of a multilateral instrument to replace the Kyoto Protocol. But at the 14th Conference of Parties (CoP 14), held in Poznan in 2008, discussions on the reliability of REDD+ focused more on the dynamics of national- and local-level actions and brought out the need to better understand, analyze and explain the national institutional context of REDD+ development. Subsequently, this review used the extractive approaches. The first inputs were reports, articles, books and documents on the DRC that were directly related to forest management, socioeconomic and political institutions, etc., whether published or not. Because of the diversity of sources, the quantitative data sometimes seem contradictory and conflictual. In the next step, semi-structured interviews were held with experts working in the forestry sector and data were obtained from the participants' observations. Since this analysis covers the period between May 2011 and June 2012 actions in the field and the institutions after those dates were not included.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".