Working papers

Academic publishing has evolved to prioritise commercial interests over knowledge sharing, often creating barriers to access and limiting how scholars can present their work. Traditional journals, while valuable for maintaining academic rigour, can constrain how we share and engage with ideas. I believe we need additional ways to communicate scholarly work that preserve academic quality while embracing more dynamic and accessible formats.

This is why I’m experimenting with a multi-version approach to publishing my academic work. Each version serves a different purpose while maintaining the core scholarly contribution:

  • Working Paper
  • Preprint version
  • Journal publication

The Working Papers on this website are “living documents” that will continue to evolve over time. They will include additional context, multimedia elements, and ongoing discussion that enrich the core academic work. This version allows me to integrate the ideas in the article more deeply with related concepts and to present it in ways that might be more meaningful for different audiences. Think of it as a more detailed story behind the research.

The preprint versions serve as formal snapshots of the article, maintaining traditional academic formatting and providing a stable reference point for citation. They represent my thinking before peer review or journal-specific modifications.

If the paper is accepted for journal publication, that version will be hosted in the relevant journal. While this version may have enhanced academic credibility through peer review, it’s important to note that all substantive scholarly content also appears in the preprint version. The journal version primarily adds the benefit of formal peer review and traditional academic recognition.


Publishing with purpose: Using AI to enhance scientific discourse

The emergence of generative AI in academic publishing presents both opportunities and risks for scientific discourse. While AI could accelerate problematic “publish or perish” incentives, it could also be used to transform scientific journals from metrics-driven repositories into vibrant learning communities that facilitate meaningful dialogue between researchers, clinicians, and educators. The article proposes specific ways AI could enhance rather than merely accelerate scientific discourse, while acknowledging the systemic challenges of implementing such changes within the current academic publishing ecosystem.