Bibliometric Analysis of the Structure and Evolution of Research on Assisted Migration
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
Abstract Purpose of Review Assisted migration is increasingly proposed as a proactive management strategy to mitigate the consequences of maladaptation predicted under climate change. Exploring the social and academic structure of the field, its research gaps, and future research directions can help further the understanding and facilitate the implementation of assisted migration strategies. Here we used bibliometric analysis to examine the intellectual, social, and conceptual structures of assisted migration research to identify gaps and opportunities for future research. Bibliometric data based on publications on assisted migration were collected from Scopus and Web of Science databases using assisted migration and climate change or their synonyms as queries. Metadata were merged, processed and several networks were constructed. Recent Findings Co-citation and keyword co-occurrence networks identified three major clusters focused on (i) theory and risk of assisted migration of threatened and endangered species, (ii) impact of climate change on realized and fundamental climate and geographic niches, and (iii) assisted population migration. Collaboration network analysis identified three social core hubs: North America, Europe, and Australia, with the USA and Canada being the most productive and the most collaborative countries. Summary We conclude that future research is expected to concern mainly the assessment of physiological response of species and populations to extreme climate events such as drought and frost, and the contribution of non-climatic factors and biotic interactions in local adaptation and population performance under climate change. Social core hubs distinguished in this work can be used to identify potential international research and training collaborators necessary to address gaps and challenges underlying assisted migration implementation.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.075 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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