Understanding the Future Green Workforce through a Corpus of Curricula Vitae from Recent Graduates
Contributo in Atti di convegno
Data di Pubblicazione:
2024
Citazione:
Understanding the Future Green Workforce through a Corpus of Curricula Vitae from Recent Graduates / Nannetti, Francesca; Di Cristofaro, Matteo. - 3878:(2024). ( 10th Italian Conference on Computational Linguistics, CLiC-it 2024 Pisa 04/12/2024-06/12/2024).
Abstract:
In view of the much-heralded ecological transition, to stay competitive and participate in the
collective effort to face global warming and climate change, organisations need to select employees
interested in and able to develop environmentally sustainable and innovative ideas. The existing
literature however does not present consistent nor concordant results on the effective interest,
involvement and expertise of Generation Z members – namely, the newest entrants into the
workforce – in green issues. This study presents a corpus-assisted methodology to explore the profile
of the upcoming workforce expected to present itself to companies. With CVs as one of the first
interfaces between candidate and company in the recruitment process, a purpose-built corpus
consisting of Curricula Vitae from recent graduates of the University of Modena and Reggio Emilia
was collected. Data is investigated through a Corpus-Assisted Discourse Studies (CADS) framework,
proposing a novel interaction between structured metadata and textual information. The original
contribution of this approach lies in the extraction of information from the narrative structure of CVs
which, guiding the evaluation and exploration of metadata, ensures that the knowledge value of the
data can be explored in a discursive manner and not reduced to lists of competences and
qualifications.
Tipologia CRIS:
Relazione in Atti di Convegno
Keywords:
Corpus Linguistics; Corpus-Assisted Discourse Studies; Curriculum Vitae; Green Workforce;
Elenco autori:
Nannetti, Francesca; Di Cristofaro, Matteo
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Link al Full Text:
Titolo del libro:
Proceedings of the Tenth Italian Conference on Computational Linguistics (CLiC-it 2024)
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