Context Assessment for Agroecology Transformation in the Tunisian Living Landscape
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of this Context Assessment is threefold: first, to characterize the environmental, social and economic and political contexts of the Tunisian ALL; second, to understand the data and information currently available in sub-region of the ALL, and third to characterize the extent to which agroecological principles are already being employed locally at the ALL levels. This report constitutes a basis of information and discussion to conduct the impact assessment. It is also valuable to all WPs in the Initiative as it provides critical quantitative or qualitative data and information regarding capacities assessment, policy influence, and other environmental attributes which can guide the initiative implementation and impact in 2023/2024. \nThe present Context Assessment in Tunisia has been elaborated from primary and secondary sources of data. The primary sources of data are issued from focus groups and formal and informal interviews conducted in the targeted area between June and December 2022, as part of WP1 and WP4 activities. The secondary sources of data came from previous research and development projects, in addition to formal and grey literature or technical reports and policy documents. This report will be enriched with a household survey planned during the first quarter of 2023. \nThis report contributes to Output 2.1. Baseline – current conditions of agricultural systems of small holder farmers in each ALL, Output 1.1 on establishment of the ALL, Output 4.1 on the identification of policies and local institutions and their role in the AE pathways.
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.
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 | 0.016 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it