Understanding the Future Green Workforce through a Corpus of Curricula Vitae from Recent Graduates Francesca Nannetti2, Matteo Di Cristofaro1 1 Department of Studies on Language and Culture, University of Modena and Reggio Emilia, 41121, Italy, IT 2 Marco Biagi Department of Economics, University of Modena and Reggio Emilia, 41121, Italy, IT 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. Keywords Corpus-Assisted Discourse Studies, Corpus Linguistics, Curriculum Vitae, Green Workforce1 1. Introduction competitive and participate in the collective effort to face global warming and climate change, organisations The pursuit of environmentally sustainable growth is need to attract, identify, select and attempt to retain now more prominently featured on the global policy individuals interested in and able to develop green and agenda than ever before [1], and the efforts to fight innovative solutions [5]. Even though by 2025 27% of the climate change and to support transition towards low or workforce will be comprised of individuals from net-zero carbon energy systems have manifested over Generation Z [6] - namely, those born roughly between the last decade through the increasing release of the mid-1990s and the early 2010s –, and despite the international agreements and strategies striving for a growing body of research on this topic [7], the existing more sustainable future [2]. literature does not present consistent nor concordant Achieving a successful transition to a more results on the effective interest, involvement and sustainable economy, however, requires not only expertise of Generation Z in sustainable and government intervention policies, but also a new environmental issues [8, 9]. Therefore, this study generation workforce [3] that should be composed of proposes a corpus-assisted methodology to explore the individuals able to deal with complex issues and Gen Z members’ profile as the newest entrants into the ambiguous situations associated with sustainable workforce, particularly considering the need for a large development in unpredictable and often rapidly and well-qualified workforce to effectively manage the changing circumstances [4]. Consequently, to stay ecological transition. Given the crucial role played by CLiC-it 2024: Tenth Italian Conference on Computational Linguistics, 0000-0001-7027-2894 (M. Di Cristofaro); 0009-0005-9197-869X (F. Dec 04 — 06, 2024, Pisa, Italy Nannetti) © 2024 Copyright for this paper by its authors. Use permitted under matteo.dicristofaro@unimore.it (M. Di Cristofaro); Creative Commons License Attribution 4.0 International (CC BY 4.0). francesca.nannetti@unimore.it (F. Nannetti) CEUR ceur-ws.org Workshop ISSN 1613-0073 Proceedings universities in educating and shaping the next applicants’ qualifications and experiences are acquired generation of professionals [10], a sample of recent over time, their personal, educational and employment graduate (2022-2023) has been identified as consistent histories are typically presented as a sequential and representative. Moreover, since in the very early progression over time. Interestingly, the author argues stages of the selection process screening applicants’ that this “introduces into the CV a temporal dimension Curricula Vitae (CVs) is a widely used recruitment that suggests a narrative” [21]. Consequently, the practice to shortlist the best candidates [11], CVs structure of a CV is designed to convey this narrative constitute the first documented interface between dimension through the co-presence of metadata with people and companies. biographical information and free fields that give the Hence, this research is based on a purpose-built candidates the opportunity to express themselves and corpus [12] consisting of 8,096 Curricula Vitae from reflect on their path. Moreover, [22] suggests that students who received a certified title at the University writing a CV implies becoming involved in acts of of Modena and Reggio Emilia during the 2022/2023 engagement and alignment to a specific landscape of academic year, collected from the AlmaLaurea database. practice. AlmaLaurea is an interuniversity Consortium Precisely with the aim of enabling a discursive representing 82 Italian universities, aimed at facilitating perspective on a corpus of CVs, it was essential to graduates’ access to the job market by helping them to imagine a data structure that would make them readable connect with companies. In this regard, one of the main by linguistic tools. services is the database of students’ Curricula Vitae. Data is investigated through a Corpus-Assisted 3. Methodology Discourse Studies (CADS) framework - that “set of studies into the form and/or function of language as As mentioned, the corpus for this study was built from communicative discourse which incorporate the use of the AlmaLaurea CVs’ database, which serves as the only computerised corpora in their analyses” [13] - serving a CV form certified by Italian universities. As such it was novel methodological approach impinging on the considered the repository offering the highest degree of interaction between CVs structured metadata and authenticity and consistency of the information textual information. reported by recent graduates. In addition, this made it possible to obtain a considerable amount of documents with the same format, thus avoiding critical issues 2. Background related to the variability of available templates. The present research draws from previous studies and theoretical frameworks related to skills and jobs geared 3.1. Corpus building workflow towards environmental sustainability; the attitude of The AlmaLaurea Information Systems Department at Generation Z towards the ecological transition; and CVs UniMoRe extracted from its database all CVs containing research value. at least one degree certified by the University of Modena The multiple dimensions discussed in the literature and Reggio Emilia during the 2022/2023 academic year. as green knowledge, green skills, green abilities, green More specifically, all those students whose CVs contain attitudes, green behaviour and green awareness [14] fall at least one with a value under a comprehensive green competence, the cognitive between January 1, 2022, and August 31, 2023, and at aspect of which seems to be the most universally least one with a value recognised and emphasised. In particular, the technical equal to University of Modena and Reggio Emilia. and analytical expertise on green issues, along with Dealing with biographical data however raises problem solving, system thinking, futures thinking and critical ethical and privacy issues; for this reason strategic thinking constitute the core of this competence AlmaLaurea conducted a preliminary data cleaning, [15, 16, 17, 18]. removing all personal references and contact details. Considering that Generation Z represents “an essential Before transmitting the files, further adjustments were stakeholder in building a sustainable future” [8], much made based on the CVs’ structure, in order to ensure discussion still revolves around whether this generation further anonymisation of the corpus. The remaining effectively has higher pro-sustainable and pro- personal data included only gender, date of birth, and environmental attitudes than the older generations [8, province of birth. Based on this information, it is not 9]. possible - in the workflow described in this paper - to In this regard, Curricula Vitae are a source of identify the individual to whom it refers, either directly information since they involve detailed and longitudinal or indirectly. data about individuals’ educational and professional Once defined which details to include from each CV backgrounds, work attitudes, personal interests and and the fields for the extraction, in December 2023 expectations [19, 20]. According to [21], since Almalaurea provided for this study 8,096 CVs structured in the English corpus. Because of this incoherence the as XML. English corpus was excluded from the analysis. Subsequently, the Italian corpus was loaded on 3.2. Data extraction and formatting #LancsBox X, which was chosen on the basis of its distinguishing feature, including its efficient metadata Extraction and formatting of the data was conducted management. Indeed, due to the nature of the dataset, through the use of a custom Python script, whose which includes 8,096 text files each one representing the function was that of producing a machine-readable XML CV of a single graduate, it was necessary to rely on a structure [23] preserving both metadata and textual tool designed to analyse linguistic data with the ability contents. The definition of the structure was informed of filtering through contextual information contained in by two different but complementary needs: first, to the metadata. allow #LancsBox X (v. 4.0.0, [24]) to manage the The software, however, does not allow the inverse resulting corpus; second, to ensure that contextual and procedure, i.e. doing quantitative analysis that is not textual information in the original dataset could be linguistic but rather informed by linguistic evidence. correctly queried and retrieved during the linguistic Thus, it is necessary to make use of data science analysis. techniques, which allow a tabular structure to be built As suggested in [25, 26], metadata were left in the from the narrative dimension [21] of CVs. Using a corpus to allow for filtering and querying procedures, custom Python script, a first attempt was made to thus exploiting the possibilities provided by the produce a data frame recording the progressive (expected) coexistence in each CV of free fields with sequence of events and details described in each CV. textual content and structured metadata. In this respect, This structure, although still preliminary, allows the it was found that a significant issue existed in the form extraction of quantitative and scalar indicators, to be of the incomplete compilation of the CVs by a combined with linguistic ones. considerable number of individuals. Only the year and An interesting example is the case of digital skills, province of birth, nationality (unspecified in 4 CVs) and which are widely assumed to be crucial for the present sex are mentioned in all 8,096 CVs. and future of occupations [29]. As shown in Tables 2 and By executing the Python script, two corpora were 3, the majority of CVs did not include these obtained – one in English (CV_En) and one in Italian competences. Of those who assessed their digital skills, (CV_It) – to accommodate the use of POS tagging. most considered themselves to be autonomous and not Using Lingua as language detector and SpaCy as advanced users. tokenizer, a check was made on the language used in each textual content of the two corpora. Results are in Table 2 Table 1. Digital competences Table 1 Commun Content Information Tokens by language ication creation processing Corpus Tok_En Tok_It None Tot No Answer 4,835 4,856 4,820 CV_it 208,233 2,771,282 36 2,979,551 None 8 40 6 Basic user 281 888 267 CV_En 233,038 271,256 4 504,298 Autonomous 1,594 1,800 2,037 user Advanced user 1,378 512 966 Tot 8,096 8,096 8,096 The relatively small percentage of Anglicisms in the Italian corpus is largely justified by the well-known presence of “English-induced lexical borrowing into Table 3 Italian” [27], in particular since the most common Digital competences domains being affected by English loanwords in the 21st Problem Safety century are economy, technology, the internet and the solving environment [27], where it is used as a “lingua franca of No Answer 4,850 4,878 communication" [28]. On the other hand, it is the None 34 106 presence of several textual fields identically collected in Basic user 836 973 each corpus but in most cases actually compiled only in Autonomous 1,831 1,754 Italian, along with textual fields effectively filled out in user English, that leads to a high percentage of Italian tokens Advanced user 545 385 Tot 8,096 8,096 powerful resource for screening biographical The final corpus loaded on #LancsBox X consists of information through textual information and vice versa. 8,096 texts, 2,597,760 grammar tokens and 2,520,735 It is in fact the combination of the two (textual data space tokens. Texts were annotated (tagged) for part of and metadata) that enables a linguistic analysis of the speech, headword and grammatical relation with SpaCy underlying narrative of CVs; a procedure that mixes model it_core_news_md v.3.7.0, while semantic tagging both qualitative and quantitative perspectives, and that was performed with PyMUSAS model can be summarised as follows. First CVs are filtered by it_dual_upos2usas_contextual v0.3.3. Accordingly, some candidates’ characteristics, starting from those well-known tools in the literature have been used to graduates that wrote a thesis concerning environmental apply a corpus-assisted methodology to the analysis of sustainability - and are therefore potentially engaged curricula vitae, thereby combining “the investigation of with topic; then the details as to how they self-assessed vast quantities of digital textual data with linguistics- themselves regarding two of the most required informed tools and frameworks of interpretation” [30]. competences in the frame of an overall green competence - capacity of initiative and problem solving - are 3.3. Data structure acquired, and triangulated with corpus analysis. Hence, drawing on a comprehensive review of the The AlmaLaurea CV contains textual fields aiding intense academic and non-academic debate on green reflections on one’s social, organisational, technical and issues, it was possible to identify some recurrent and artistic competences and outlining a personal significant topic that would return abstracts relevant to description of oneself. In addition, applicants are asked the present analysis. Once a subcorpus with all abstracts to indicate their professional objective and desired (3,724) was created on LancsBox X, through wildcard occupation. With regard to the educational and searches in both English and Italian, the following words professional pathway, it is required to reflect on the and their derivatives from the same root were identified: competences acquired during these experiences. An sostenibilità/ sustainability (sostenibil*/ sustainab*), emphasis is also placed on the thesis work, for which the cambiamento/ change (cambiament*/ change*), title, keywords and abstract are requested. For example, transizione/ transition (transizion*/ transition*), Figure 1 and Figure 2 show excerpts from CVs in which energia/energy (energ*). Results are summarized in Table the sections relating to the professional objective and 4. desired occupation have been filled. Table 4 Wildcard searches in thesis abstracts Value Hits Texts sostenibil*/sustainab* 789 439 cambiament*/change* 640 474 energ* 569 356 transizion*/transition* 152 102 Figure 1: Professional objective and desired occupation Tot 2,150 1,371 in 006101_it. Therefore, since collocates are “words which frequently co-occur, more often than would otherwise be expected by chance alone” [31] and collocation analysis is often used to identify discourses in corpus linguistics, collocates of the aforementioned occurrences are presented in Figure 3, 4, 5, 6. Given the prevalence of Italian occurrences, apart from the search for energ*, in all the other cases the collocates of the Italian terms are Figure 2: Professional objective and desired occupation shown. More specifically, the first 20 are displayed, with in 002746_it. stop words removed, Freq.(collocation) >5 and Log Dice >6. As shown in Figure 1 and 2, the wealth of available metadata - biographical information, the educational and professional background, self-assessment of personal attitudes and also preferences with respect to professional career development - arguably represents a Figure 6: GraphColl for energ* in subcorpus Figure 3: GraphColl for sostenibil* in subcorpus “tesiabstract_it” “tesiabstract_it” From collocation analysis it emerged that, ranked by Log Dice, the first 4 collocation are: transizione energetica (11,6) transizione ecologica (11,4), cambiamento climatico (11,4) and sostenibilità ambientale (10,8). Deeply zooming in into candidates’ characteristics, the analysis moved to observing how graduates that included these phrases into their CV’s textual fields - and therefore seem to be involved in the topic - self-assessed themselves regarding capacity of initiative and problem solving. Results are in Figure 7. Phrase self asssesment (0-10) Problem solving Capacity for initiative transizione energetica 0 5 5 6 1 1 7 0 2 8 4 4 9 5 3 10 3 3 transizione ecologica 0 5 5 Figure 4: GraphColl for cambiament* in subcorpus 7 1 1 “tesiabstract_it” 8 5 5 9 3 3 10 2 2 cambiamento climatico 0 14 14 5 0 1 7 5 1 8 11 15 9 8 7 10 7 7 sostenibilità ambientale 0 11 11 6 1 3 7 6 6 8 18 11 9 12 17 10 6 6 Tot_CVs 133 133 Figure 7: Self-assessment scores for capacity for initiative and problem solving Figure 5: GraphColl for transizion* in subcorpus It is worth noting that many students did not fill “tesiabstract_it” these fields, despite their widely recognised importance. Among those who did fill them in, there does not appear to be a prevailing feeling of excellence in these skills, but rather a cautious confirmation. 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