Territorial intelligence in Algeria, between network structuring and sustainable development
Bibliographic record
Abstract
Territorial intelligence in Algeria represents a captivating and crucial field of study, situated at the intersection of network structuring and sustainable development. In a context where territories play a vital role in achieving national objectives, territorial intelligence emerges as a strategic component. This study explores the complex dynamics related to the network structuring of territorial actors and its impact on sustainable development. Algeria, with its geographical, social, and economic diversity, provides a fertile ground to understand how territorial intelligence can catalyze cooperation among different actors and promote sustainable initiatives. This exploration will seek to shed light on the challenges and opportunities presented by territorial intelligence in the specific context of Algeria, emphasizing its potential role as a lever for harmonious and sustainable development. This work pursues two fundamental objectives. Firstly, it aims to clarify the concept of territorial intelligence by highlighting its collective, transformative, and interactionist dimensions. We have endeavored to demonstrate the existence of interdependencies and reciprocal links between the network structuring of actors and the local industrial dynamics. Secondly, we delve into the question of sustainable development in territories in Algeria, particularly in the province of Blida, known for its specific entrepreneurial dynamics. Our exploratory study is based on a quantitative statistical survey through a questionnaire, conducted with a sample of 110 companies located in various industrial and business zones in the province of Blida. The main results of this research highlight that the geographical concentration of companies provides an opportunity to strengthen competitive interactions and foster the emergence of ecosystems conducive to exchange, knowledge transfer, innovation, and the creation of added value at the local level. We observe that the deployment of territorial intelligence and network structuring processes requires a specific industrial organization, including the establishment of open and collaborative networks or clusters of companies. JEL Classification: D21, L10, O31, R11
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".