The IDEA Method for Assessing Irrigated Cereal Farms Sustainability in Algerian Arid Zones: Case of Ouargla Region (Oued M'ya)
Bibliographic record
Abstract
The agricultural sector in the Saharan regions of Algeria has seen, since 1983, the development program of cereal cultivation irrigated by pivots thanks, essentially, to the availability of underground water resources which constitute its keystone. In Ouargla, these farms strongly supported by the public authorities and sustained by neo-farmers have marked progressions and regressions in space and in time, some have disappeared, others have undergone changes thus calling into question their durability. This research aims to assess the sustainability of these farms by the IDEA method (Sustainability Indicators of Farms Agricultural- Indicateurs de Durabilité des Exploitations Agricoles) based mainly on three scales; the agro-ecological scale, the socio-territorial scale and the economic scale. The analysis of 13 farms shows that this is an artificial production system, the installation of which is at great risk and depends heavily on the will of agricultural policies and entrepreneur-farmers. The economic scale seems to have the best score, however the profits generated by the farmers can be explained more by the consistent support of the State than by a tangible accounting balance. At the socio-territorial level, most of the components are failing, in particular a very low diversity of products and a strong lack of employment. The agroecological scale constitutes the limiting factor par excellence with an agriculture which consumes a lot of non-renewable water and energy and at the same time destroys the soil resource by the phenomenon of salinization. Thus the three scales are failing and the limiting factor par excellence is the environmental scale, the consideration of which is strongly recommended both nationally and internationally. This research also highlights the need for a revision of certain indicators of the IDEA method with a view to adapting it to the local context of arid zones and to the cereal agrosystem in Ouargla.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".