ArticleScientific reports2025
Anatomy of climate change research in Italian doctoral dissertations using a machine learning approach.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Climate change is one of the defining challenges of our time, yet little is known about how early-career researchers contribute to this field through doctoral research. This study provides the first comprehensive mapping of climate change-related doctoral dissertations in Italy across all disciplines, spanning a 14-year period (2008-2021). Doctoral dissertations offer a unique lens into the formative stages of scientific inquiry, where new ideas, methods, and agendas take shape. Using a machine learning approach on a novel dataset of over 74,394 dissertations, we conduct the first large-scale classification of climate change dissertations in Italy. We identify climate-related dissertations and analyze their thematic, disciplinary, and geographical distribution, highlighting emerging research trends in areas such as energy transition, biodiversity conservation, and extreme weather events. While technical disciplines dominate among English-language dissertations, those written in Italian reveal a more balanced disciplinary landscape, with a stronger presence of the social sciences and humanities-though these remain underrepresented overall. Although climate-related research spans a variety of topics, regional variation also emerges: water in the North, energy in the Centre and South, and governance in the Islands. This study marks an important step toward recognizing doctoral research as a strategic asset in building resilient climate knowledge systems and guiding long-term policy planning.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.