Where workers and communities drive the green transition: meso-level evidence on the competences Europe needs

Green Pulse — Polyphonic Up/reskilling for Living Skills Ecosystems

To build a boat is not about weaving the sails, forging the nails, or reading the stars; to build a boat is about birthing a common desire for the sea in our hearts.
Antoine de Saint-Exupéry, Citadelle, Chapter LXXV (1948)

HORIZON-CL2-2026-01-TRANSFO-07

“Most available research on the green transition focuses on macro-level policies, overlooking how workers and communities can drive change.”

— European Commission, Work Programme 2026

The problem TRANSFO-07 sets — and where the meso level fits

Everyone agrees skills matter. Almost no one is in training.

95%

of EU SMEs call having workers with the right skills important to their business model.

Flash Eurobarometer, 2023

~12%

of adults are in any education or training in a given month — far below the EU's 60%-by-2030 goal.

Eurostat LFS, 2022

“no need”

is the single most common reason adults give for not training — they don't see a need for themselves.

Eurostat Adult Education Survey

And the need is not marginal. For the twin transition Cedefop finds all occupations will need at least some up- or reskilling; about half of workers face a digital skills gap; and 27% are in “dead-end jobs” — more skilled than their work allows them to use. (Cedefop European Skills & Jobs Survey)

TRANSFO-07 itself notes that most research “focuses on macro-level policies, overlooking how workers and communities can drive change.” The two decades of EU competence frameworks — DigComp, EntreComp, LifeComp, and now GreenComp — describe competence at that macro level, as a taxonomy a worker is matched against. They are indispensable for comparison, but they are read against the meso level — sectors, workplaces, communities of practice — where the gap above actually lives and where the call asks for evidence.

GreenPulse’s contribution is to add that missing layer. Competence is treated not only as a structure a worker has but as an operation a worker does — captured in situ, in their own account, and only then mapped onto ESCO / GreenComp / DigComp as an output, never an input. Narrative, operation-first collection grounds and defines the variables the large EU quantitative instruments (Cedefop’s skills survey, Skills-OVATE) then scale — qualitative and quantitative, as the call requires.

Outcome 1

Which competences workers need

Meso-level competence statements for the energy transition — what workers actually use, not what policy presumes.

Outcome 2

Actionable E&T & policy advice

Competence-pathway briefs and VET-curriculum updates, gender- and disability-inclusive, feeding the Union of Skills and Pact for Skills.

Outcome 3

Green ↔ digital interconnection

The twin-transition interface read where it is densest — grid-data literacy, AI-fluency and copilot workflows in energy operations.

The aim: an evidence apparatus that makes the competences of incumbent, young, disabled and marginalised workers legible where the taxonomies read only deficit. See the full call coverage.

Coordinated by

Conservatoire national des arts et métiers

Established 10 October 1794·230+ years of continuous lifelong learning·the oldest of its kind still in service

Founded by decree of the Convention nationale, on Abbé Henri Grégoire’s proposal, to keep the arts and crafts — and teach them to working adults. GreenPulse builds on its unbroken 230-year record of evidence on industrial transition, competence and labour.

Why energy — single-sector focus

The sector TRANSFO-07 must answer

Cedefop demand-validated

Cedefop’s Skills in transition to 2035 places energy among the sectors most reshaped by Green-Deal skills demand.

Regional anchors ready

Norrbotten (green steel + H2) and Grand Est (white hydrogen exploration): live transitions on diverging technology pathways. Replicability built in.

Twin-transition spine

The green-digital interface is densest in energy: grid-data literacy, AI-fluency for renewables operations, copilot workflows on industrial software. Strongest ground for Outcome 3.

Narrative-evidence ancestry

The best-documented sector in the narrative-evidence literature: Moezzi · Janda · Rotmann (2017), Towers · Chabay · Okada (2022), Sleigh on carbon-economy decline, the Helgeson observatory family.

Nuclear branch — cross-cutting both anchors

Both anchor nations run major nuclear fleets and are building new capacity: France’s Grand Est (Cattenom, Chooz) and Sweden (Forsmark · Ringhals, plus planned new-build and SMRs). Decommissioning, life-extension, new-build and SMR work form a distinct competence branch — high-stakes, slow-clock, safety-critical operations the taxonomies capture poorly — running across both regions.

Lowest-risk, highest-citability single-sector choice for TRANSFO-07. Multi-sector scaling can follow.

Fieldwork locations — Three energy phenomena

Industrial electrification — Norrbotten, Sweden · Green steel production & heavy manufacturing electrification

Industrial electrification

Norrbotten, Sweden · Green steel production & heavy manufacturing electrification

Renewable integration — Grand Est, France · Industrial heat recovery, energy-intensive manufacturing transition

Renewable integration

Grand Est, France · Industrial heat recovery, energy-intensive manufacturing transition

Nuclear branch — France & Sweden · New-build, decommissioning & SMR — safety-critical, slow-clock competences

Nuclear branch

France & Sweden · New-build, decommissioning & SMR — safety-critical, slow-clock competences

Picking up where EU work left us

A decade of EU skills research mapped the demand.GreenPulse identifies the competences, explains why gaps reproduce, and translates findings into policy.

Cedefop · JRC · SkillsPULSE · BRIDGES 5.0 · the energy-citizenship cluster · the H2020 coal quartet — Europe has built an extraordinary quantitative baseline on green-transition skill demand. GreenPulse does not duplicate it. We carry it forward with what TRANSFO-07 explicitly asks for: identification of meso-level competence evidence, actionableE&T and policy guidance (including gender, disability and age-of-intervention dimensions), and operational green-digital competence integration.

EU research has built

Quantitative baseline

  • Cedefop ESJS2 — internal skill-gap microdata (EU-wide)
  • SkillsPULSE D2.1+D2.2 — three-layer mismatch taxonomy on vacancy-NLP
  • Lightcast online job-vacancy corpus — AI-skill demand signals
  • OSKA · EDUFI · UK Unit for Future Skills — national foresight templates
  • JRC twin-transitions report · Cedefop Skills in transition to 2035 — EU-policy anchor

What the baseline cannot see

The persistent blind spot

  • Which competences workers actually use at the meso-level — beyond aggregate vacancies
  • Why structural shortages reproduce where and how they do
  • How workers narrate competence to themselves and others — and where GreenComp frames land or don't
  • What the first prompt, dial-turn, agent-reply reveal about competence-in-formation
  • How to translate evidence into E&T curriculum + policy briefs civil servants and social partners can actually use

Evidence × explanation × policy

What GreenPulse adds

  • Outcome 1 — Atlas of Transitions: meso-level competence map per anchor region, cross-walked to GreenComp's 12 competences and the SkillsPULSE mismatch taxonomy
  • Outcome 2 — Policy Integration Roadmap + Messaging Toolkit: dated, costed competence-pathway briefs to DG CLIMA · DG EMPL · DG RTD, with disability + gender + age tracks (GRBC, Academies)
  • Outcome 3 — SED-PAN Digital-Green Competence Matrix + OSDEM human-agent dialogue capture (LLM copilots logged as competence evidence)
  • NECx narrative-cascade workshops + Historical-Archival fieldwork (CNAM · MUAM) — the meso-level evidence base no other consortium will field
  • Mandatory dimensions woven in: STR Partnership · Erasmus+ · Pillar of Social Rights 2030 · NEB Facility · open-science via EOSC

The handoff in one sentence

SkillsPULSE measures what skill is missing. GreenPulse identifies the meso-level competence, explains why the gap reproduces, and delivers the policy briefs and curriculum updates that close it.

Three TRANSFO-07 outcomes, three operational answers — Atlas of Transitions (identification), Policy Integration Roadmap + Toolkit (E&T + policy translation), SED-PAN + OSDEM (green-digital). Both quantitative and qualitative methods sit inside the consortium: SkillsPULSE through Università di Pisa (partner); BRIDGES 5.0 (€4.6M, CL4) through CNAM (beneficiary, finishing Dec 2026 — its results arrive as GreenPulse starts). The handoff is not a promise. It is built into the consortium roster.

See the full clustering map for the ~30 EU projects GreenPulse webs into across 7 tiers.

Confirmed consortium

12 partners · 8 countries + 1 international · 6 consortium roles

Academic & Heritage
CNAMUniversity of WarsawUniversità di PisaRīgas Stradiņš University
Research Institute
Green Economics InstituteETUI
Cultural Institution
MUAM
Civil Society
ENOP
Youth Organisation
ZOCGGYG
SME
QUIZASPolygon

4 advisory / gap roles still open — see Partners.

Geographic footprint

Where the consortium reaches

Drag to pan · scroll / pinch to zoom · hover any partner country for detail

3 continents · 12 partners

Consortium partner countryCNAM Centers · 23 countries

🇪🇺EU member states

🇫🇷FR🇧🇪BE🇱🇻LV🇵🇱PL🇮🇹IT

Future EU · accession 2028

🇲🇪

Montenegro

ZOCG

🌐Associated / international

🇨🇦CA🇬🇧GB🌐INT

CNAM Centers · institutional reach of the coordinator

23 countries · 4 continents · Métropole + DROM-COM

Algérie · Bénin · Burkina Faso · Burundi · Cameroun · Chine · Côte d’Ivoire · Djibouti · France (Métropole + Guadeloupe · Martinique · Guyane · Réunion · Mayotte · Nouvelle-Calédonie · Polynésie française) · Gabon · Guinée · Liban · Madagascar · Mali · Maroc · Mauritanie · Niger · République centrafricaine · République du Congo · Sénégal · Togo · Tunisie

Coordinator’s teaching + partner-centre footprint. Distinct from the GreenPulse consortium partner countries above; shown to indicate scale of CNAM’s institutional reach.