Capability findings

What learning, practicum and workforce evidence show, in aggregate, each with its source.

In preparation. This RA chapter is not written yet; it holds no findings.
Contents
  1. ·Edition home
  2. 1Capability needed
  3. 2Capability findings
    1. 2.1 What this chapter will report
    2. 2.2 Where the evidence sits now
    3. 2.3 Contribute to this chapter
  4. 3Faculties and roles
  5. 4Gaps and pathways
  6. 5Workforce scenarios
  7. 6Readings from the other desks
  8. 7Curriculum agenda
  9. 8Competency map

2.1What this chapter will report

What learning, practicum and workforce evidence show, in aggregate, each with its source.

It answers the frame question "findings" in the terms of Academy Capability, so the Collection can set it beside chapter 2 of the other desks’ editions.

2.2Where the evidence sits now

The nearest material today is chapter 2 of the Global Centre for Risk and Innovation (GCRI) Systems Evidence edition for Neurotechnology and Human–Machine Interfaces: findings. It is a cross-reference, not a copy, and it is a draft in stewardship review.

Downloads

The print edition of the evidence this chapter cross-references: the GCRI Systems Evidence edition for Neurotechnology and Human–Machine Interfaces.

Draft, not yet releasedThe print and files of the GCRI edition this desk’s edition cross-references. Review copies until release; the DOI is issued at deposit.

  • Print

    • PDF, A4

      The GCRI Systems Evidence print edition for this subject, A4: cover, imprint, contents with page numbers, every chapter and annex.

      PDF113 pages1.1 MBTagged, with bookmarks

      SHA-256 1b276afce6bca24b54678af9a98bba706f7ae5b11f20c2e49c30c56bd83684a0

    • PDF, US Letter

      The GCRI Systems Evidence print edition for this subject, US Letter: cover, imprint, contents with page numbers, every chapter and annex.

      PDF121 pages1.1 MBTagged, with bookmarks

      SHA-256 d43ae78f5a47684feb2d0ecc78a28696fdf3670c30a7369d28936ab2abf77a4a

  • Web edition

  • Data bundle

    • Indicators, CSV

      16 indicators with unit, year, status and source

      NR-XTECH-NEURO-GLOBAL-2026-BASELINE-indicators.csv1 KB

      SHA-256 5fcebba27a41f952eb1984a1849d9a21e636ecbbb858a7cfd12593273299e02e

    • Indicators, JSON

      The same indicators with the edition’s identity and licence

      NR-XTECH-NEURO-GLOBAL-2026-BASELINE-indicators.json2 KB

      SHA-256 84763ac2fc518c6e22a607df96e5cf665b378b7e2d5dae3a93a829a6138395b1

    • Findings, CSV

      12 findings with status, evidence-quality level and references

      NR-XTECH-NEURO-GLOBAL-2026-BASELINE-findings.csv3 KB

      SHA-256 99d3e17ea329a61d07269b9c4fb66f9314005dd8eda895cb760a597a576e78e1

  • Citation files

    • Citation, BibTeX

      For LaTeX and reference managers

      NR-XTECH-NEURO-GLOBAL-2026-BASELINE.bib1 KB

      SHA-256 1dde833e8119208f178aeefbcf409f286888583c46d261fd832b153c63a7f09a

    • Citation, RIS

      For Zotero, EndNote and Mendeley

      NR-XTECH-NEURO-GLOBAL-2026-BASELINE.ris1 KB

      SHA-256 35894c37df1d75bc5661eec8b7840ebf4685defc55be5acceb4648e7b70de89d

    • Citation, CITATION.cff

      Citation File Format 1.2.0, for GitHub, Zenodo and software catalogues

      NR-XTECH-NEURO-GLOBAL-2026-BASELINE.cff1 KB

      SHA-256 fe34e2f10f3e0a3621cd4df996367019140db054e8d7d94f0890286aba3f630e

Check a file with its SHA-256: shasum -a 256 <file> (macOS, Linux) or Get-FileHash <file> (Windows). Text, tables and figures by Nexus: CC BY 4.0; each source keeps its own licence.

2.3Contribute to this chapter

The capability of the workforce that manages the risks in scope: the competencies needed, what learning and practicum show, and where the gaps are. Reported in aggregate only; no learner record is published. Material for this chapter goes to the Academy Capability desk; what belongs to another desk is forwarded, not refused.

Risk Academy reads an edition for capability: what competence exists, what is missing, which pathway closes the gap and which role needs it.

If you teach or assess risk, send aggregate outcomes and the method behind them. The Academy will not accept a file that names a learner.

ReportsContribute

Contribute to chapter 2 of Capability: Neurotechnology and Human–Machine Interfaces 2026.

Reports is the Consortium’s quarterly publication, written by six desks. This page sits with the Academy Capability desk. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work. Sent to the wrong desk, it is forwarded, not refused.

Academy Capability deskAcademy Capability

CC BY 4.0 Free to read. Text and figures: CC BY 4.0. Data: CC0 1.0. Authors keep copyright. Published by GCRI Canada.

Your role here

What you can do from this page.

  • ReaderFound an error? Every correction is public.Corrections log
  • ContributorSend evidence, data or a correction to this desk.Contribute
  • ReviewerReview for this desk; verified reviews are credited.Become a reviewer
  • Editor, steward or boardQueues, decisions and production are in the workspace.My workspace
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