Odyssey of First IALE World Congress in Africa and Opportunities for North-South or South-South Collaboration
Bibliographic record
Abstract
The landscape ecology community witnessed a landmark event in July 2023 as the 11th International Association for Landscape Ecology (IALE) World Congress unfolded on the African continent for the first time. This editorial commemorates this historic occasion, tracing the journey from the inception of Africa-IALE initiatives in 2002 to the culmination of the World Congress held in Nairobi, Kenya, almost two decades later. Having previously graced Europe, Northern America, Australia, and Asia, the IALE World Congress embraced Africa, showcasing the global reach and inclusive spirit of landscape ecology. This editorial explores the evolution of Africa-IALE, highlighting the initiatives and the persistent efforts that led to the World Congress in Africa. We firstly delve into the socio-cultural and international significance of this shift, emphasising the unique perspectives and challenges faced by the African landscape ecology community. Secondly, we assess the participants involved in the 11th World IALE Congress, the topics discussed, current trends, and priorities within the global landscape ecology research community. To do so, we conducted a bibliometric analysis of the conference proceedings. Lastly, we reflect on the impacts of this Congress. Our retrospective perspective offers a comprehensive view of the symbiotic relationships among the international landscape ecology community and how landscape ecology has evolved in parallel with emerging challenges and emerging centres of knowledge and leadership.
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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".