CONSTRUCTION WITH BAMBOO AS A TOOL FOR RESEARCH-BASED SOCIAL DEVELOPMENT: A SUSTAINABLE LIVELIHOODS ANALYSIS
Bibliographic record
Abstract
Bamboo is a natural building material that grows widely across the tropics and subtropics. It has been used in traditional construction for millennia and is now used in a growing range of innovative bio-based building solutions. Citing bamboo’s potential for carbon capture, promising physical properties and relative underdevelopment of the global bamboo industry, many projects and initiatives have been launched that aim to develop bamboo industries to support livelihood development. These projects use a wide range of implementation strategies. Using theory-based program evaluation based on the Sustainable Livelihoods Framework, this paper focuses on three case studies from Costa Rica, Nigeria, and Indonesia. Each case study employs different strategies for research for social development and utilized the harvest, processing and manufacture of bamboo construction materials and products. First, a low-cost self-help construction project in Costa Rica is described. Next, a bamboo architecture community development project in Indonesia using participatory action research is analyzed. The final strategy uses community-based action research to develop bamboo-based prototypes of vertical greening systems in Nigeria. In each case study, bamboo is selected as an affordable and locally available material. The projects are evaluated using logic models and the core principles of the Framework. This paper demonstrates applications of the Sustainable Livelihoods Framework and other theory-based evaluation frameworks to analyze research-for-development and social projects.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.013 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.019 | 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".