What is the role of data in jobs in the United Kingdom, Canada, and the United States?: A natural language processing approach
This paper estimates the data intensity of occupations/sectors (i.e. the share of job postings per occupation/sector related to the production of data) using natural language processing (NLP) on job advertisements in the United Kingdom, Canada and the United States. Online job advertisement data col...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Weitere Verfasser: | , |
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Paris
OECD Publishing
2023
|
| Schriftenreihe: | OECD Statistics Working Papers
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | This paper estimates the data intensity of occupations/sectors (i.e. the share of job postings per occupation/sector related to the production of data) using natural language processing (NLP) on job advertisements in the United Kingdom, Canada and the United States. Online job advertisement data collected by Lightcast provide timely and disaggregated insights into labour demand and skill requirements of different professions. The paper makes three major contributions. First, indicators created from the Lightcast data add to the understanding of digital skills in the labour market. Second, the results may advance the measurement of data assets in national account statistics. Third, the NLP methodology can handle up to 66 languages and can be adapted to measure concepts beyond digital skills. Results provide a ranking of data intensity across occupations, with data analytics activities contributing most to aggregate data intensity shares in all three countries. At the sectoral level, the emerging picture is more heterogeneous across countries. Differences in labour demand primarily explain those variations, with low data-intensive professions contributing most to aggregate data intensity in the United Kingdom. Estimates of investment in data, using a sum of costs approach and sectoral intensity shares, point to lower levels in the United Kingdom and Canada than in the United States |
| Beschreibung: | 1 Online-Ressource (45 Seiten) 21 x 28cm |
| DOI: | 10.1787/fa65d29e-en |
Internformat
MARC
| LEADER | 00000nam a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV050074438 | ||
| 003 | DE-604 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 241209s2023 xx o|||| 00||| eng d | ||
| 024 | 7 | |a 10.1787/fa65d29e-en |2 doi | |
| 035 | |a (ZDB-13-SOC)098549987 | ||
| 035 | |a (DE-599)BVBBV050074438 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-384 |a DE-91 |a DE-473 |a DE-824 |a DE-29 |a DE-739 |a DE-355 |a DE-20 |a DE-1028 |a DE-1049 |a DE-188 |a DE-521 |a DE-861 |a DE-898 |a DE-92 |a DE-573 | ||
| 100 | 1 | |a Schmidt, Julia |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a What is the role of data in jobs in the United Kingdom, Canada, and the United States? |b A natural language processing approach |c Julia, Schmidt, Graham, Pilgrim and Annabelle, Mourougane |
| 264 | 1 | |a Paris |b OECD Publishing |c 2023 | |
| 300 | |a 1 Online-Ressource (45 Seiten) |c 21 x 28cm | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a OECD Statistics Working Papers | |
| 520 | |a This paper estimates the data intensity of occupations/sectors (i.e. the share of job postings per occupation/sector related to the production of data) using natural language processing (NLP) on job advertisements in the United Kingdom, Canada and the United States. Online job advertisement data collected by Lightcast provide timely and disaggregated insights into labour demand and skill requirements of different professions. The paper makes three major contributions. First, indicators created from the Lightcast data add to the understanding of digital skills in the labour market. Second, the results may advance the measurement of data assets in national account statistics. Third, the NLP methodology can handle up to 66 languages and can be adapted to measure concepts beyond digital skills. Results provide a ranking of data intensity across occupations, with data analytics activities contributing most to aggregate data intensity shares in all three countries. At the sectoral level, the emerging picture is more heterogeneous across countries. Differences in labour demand primarily explain those variations, with low data-intensive professions contributing most to aggregate data intensity in the United Kingdom. Estimates of investment in data, using a sum of costs approach and sectoral intensity shares, point to lower levels in the United Kingdom and Canada than in the United States | ||
| 650 | 4 | |a Employment | |
| 650 | 4 | |a Economics | |
| 650 | 4 | |a Canada | |
| 650 | 4 | |a United Kingdom | |
| 650 | 4 | |a United States | |
| 700 | 1 | |a Pilgrim, Graham |4 ctb | |
| 700 | 1 | |a Mourougane, Annabelle |4 ctb | |
| 856 | 4 | 0 | |u https://doi.org/10.1787/fa65d29e-en |x Verlag |z kostenfrei |3 Volltext |
| 912 | |a ZDB-13-SOC | ||
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-035411800 | |
Datensatz im Suchindex
| _version_ | 1817990476219809792 |
|---|---|
| adam_text | |
| any_adam_object | |
| author | Schmidt, Julia |
| author2 | Pilgrim, Graham Mourougane, Annabelle |
| author2_role | ctb ctb |
| author2_variant | g p gp a m am |
| author_facet | Schmidt, Julia Pilgrim, Graham Mourougane, Annabelle |
| author_role | aut |
| author_sort | Schmidt, Julia |
| author_variant | j s js |
| building | Verbundindex |
| bvnumber | BV050074438 |
| collection | ZDB-13-SOC |
| ctrlnum | (ZDB-13-SOC)098549987 (DE-599)BVBBV050074438 |
| discipline | Wirtschaftswissenschaften |
| doi_str_mv | 10.1787/fa65d29e-en |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00000nam a2200000zc 4500</leader><controlfield tag="001">BV050074438</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">241209s2023 xx o|||| 00||| eng d</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1787/fa65d29e-en</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-13-SOC)098549987</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV050074438</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-384</subfield><subfield code="a">DE-91</subfield><subfield code="a">DE-473</subfield><subfield code="a">DE-824</subfield><subfield code="a">DE-29</subfield><subfield code="a">DE-739</subfield><subfield code="a">DE-355</subfield><subfield code="a">DE-20</subfield><subfield code="a">DE-1028</subfield><subfield code="a">DE-1049</subfield><subfield code="a">DE-188</subfield><subfield code="a">DE-521</subfield><subfield code="a">DE-861</subfield><subfield code="a">DE-898</subfield><subfield code="a">DE-92</subfield><subfield code="a">DE-573</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Schmidt, Julia</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">What is the role of data in jobs in the United Kingdom, Canada, and the United States?</subfield><subfield code="b">A natural language processing approach</subfield><subfield code="c">Julia, Schmidt, Graham, Pilgrim and Annabelle, Mourougane</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Paris</subfield><subfield code="b">OECD Publishing</subfield><subfield code="c">2023</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (45 Seiten)</subfield><subfield code="c">21 x 28cm</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">OECD Statistics Working Papers</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This paper estimates the data intensity of occupations/sectors (i.e. the share of job postings per occupation/sector related to the production of data) using natural language processing (NLP) on job advertisements in the United Kingdom, Canada and the United States. Online job advertisement data collected by Lightcast provide timely and disaggregated insights into labour demand and skill requirements of different professions. The paper makes three major contributions. First, indicators created from the Lightcast data add to the understanding of digital skills in the labour market. Second, the results may advance the measurement of data assets in national account statistics. Third, the NLP methodology can handle up to 66 languages and can be adapted to measure concepts beyond digital skills. Results provide a ranking of data intensity across occupations, with data analytics activities contributing most to aggregate data intensity shares in all three countries. At the sectoral level, the emerging picture is more heterogeneous across countries. Differences in labour demand primarily explain those variations, with low data-intensive professions contributing most to aggregate data intensity in the United Kingdom. Estimates of investment in data, using a sum of costs approach and sectoral intensity shares, point to lower levels in the United Kingdom and Canada than in the United States</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Employment</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Economics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Canada</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">United Kingdom</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">United States</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Pilgrim, Graham</subfield><subfield code="4">ctb</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mourougane, Annabelle</subfield><subfield code="4">ctb</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1787/fa65d29e-en</subfield><subfield code="x">Verlag</subfield><subfield code="z">kostenfrei</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-13-SOC</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-035411800</subfield></datafield></record></collection> |
| id | DE-604.BV050074438 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-09T19:00:24Z |
| institution | BVB |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-035411800 |
| open_access_boolean | 1 |
| owner | DE-384 DE-91 DE-BY-TUM DE-473 DE-BY-UBG DE-824 DE-29 DE-739 DE-355 DE-BY-UBR DE-20 DE-1028 DE-1049 DE-188 DE-521 DE-861 DE-898 DE-BY-UBR DE-92 DE-573 |
| owner_facet | DE-384 DE-91 DE-BY-TUM DE-473 DE-BY-UBG DE-824 DE-29 DE-739 DE-355 DE-BY-UBR DE-20 DE-1028 DE-1049 DE-188 DE-521 DE-861 DE-898 DE-BY-UBR DE-92 DE-573 |
| physical | 1 Online-Ressource (45 Seiten) 21 x 28cm |
| psigel | ZDB-13-SOC |
| publishDate | 2023 |
| publishDateSearch | 2023 |
| publishDateSort | 2023 |
| publisher | OECD Publishing |
| record_format | marc |
| series2 | OECD Statistics Working Papers |
| spelling | Schmidt, Julia Verfasser aut What is the role of data in jobs in the United Kingdom, Canada, and the United States? A natural language processing approach Julia, Schmidt, Graham, Pilgrim and Annabelle, Mourougane Paris OECD Publishing 2023 1 Online-Ressource (45 Seiten) 21 x 28cm txt rdacontent c rdamedia cr rdacarrier OECD Statistics Working Papers This paper estimates the data intensity of occupations/sectors (i.e. the share of job postings per occupation/sector related to the production of data) using natural language processing (NLP) on job advertisements in the United Kingdom, Canada and the United States. Online job advertisement data collected by Lightcast provide timely and disaggregated insights into labour demand and skill requirements of different professions. The paper makes three major contributions. First, indicators created from the Lightcast data add to the understanding of digital skills in the labour market. Second, the results may advance the measurement of data assets in national account statistics. Third, the NLP methodology can handle up to 66 languages and can be adapted to measure concepts beyond digital skills. Results provide a ranking of data intensity across occupations, with data analytics activities contributing most to aggregate data intensity shares in all three countries. At the sectoral level, the emerging picture is more heterogeneous across countries. Differences in labour demand primarily explain those variations, with low data-intensive professions contributing most to aggregate data intensity in the United Kingdom. Estimates of investment in data, using a sum of costs approach and sectoral intensity shares, point to lower levels in the United Kingdom and Canada than in the United States Employment Economics Canada United Kingdom United States Pilgrim, Graham ctb Mourougane, Annabelle ctb https://doi.org/10.1787/fa65d29e-en Verlag kostenfrei Volltext |
| spellingShingle | Schmidt, Julia What is the role of data in jobs in the United Kingdom, Canada, and the United States? A natural language processing approach Employment Economics Canada United Kingdom United States |
| title | What is the role of data in jobs in the United Kingdom, Canada, and the United States? A natural language processing approach |
| title_auth | What is the role of data in jobs in the United Kingdom, Canada, and the United States? A natural language processing approach |
| title_exact_search | What is the role of data in jobs in the United Kingdom, Canada, and the United States? A natural language processing approach |
| title_full | What is the role of data in jobs in the United Kingdom, Canada, and the United States? A natural language processing approach Julia, Schmidt, Graham, Pilgrim and Annabelle, Mourougane |
| title_fullStr | What is the role of data in jobs in the United Kingdom, Canada, and the United States? A natural language processing approach Julia, Schmidt, Graham, Pilgrim and Annabelle, Mourougane |
| title_full_unstemmed | What is the role of data in jobs in the United Kingdom, Canada, and the United States? A natural language processing approach Julia, Schmidt, Graham, Pilgrim and Annabelle, Mourougane |
| title_short | What is the role of data in jobs in the United Kingdom, Canada, and the United States? |
| title_sort | what is the role of data in jobs in the united kingdom canada and the united states a natural language processing approach |
| title_sub | A natural language processing approach |
| topic | Employment Economics Canada United Kingdom United States |
| topic_facet | Employment Economics Canada United Kingdom United States |
| url | https://doi.org/10.1787/fa65d29e-en |
| work_keys_str_mv | AT schmidtjulia whatistheroleofdatainjobsintheunitedkingdomcanadaandtheunitedstatesanaturallanguageprocessingapproach AT pilgrimgraham whatistheroleofdatainjobsintheunitedkingdomcanadaandtheunitedstatesanaturallanguageprocessingapproach AT mourouganeannabelle whatistheroleofdatainjobsintheunitedkingdomcanadaandtheunitedstatesanaturallanguageprocessingapproach |