Voices at the Margins: Podcasting as Neuroqueer Collaborative Autoethnography and Epistemic Healing

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Hughes, C., Wells, C., Nicholson, E., Mayhew, B., Gay, S., Kammersell, M., & Mogler, T. (2026). Voices at the Margins: Podcasting as Neuroqueer Collaborative Autoethnography and Epistemic Healing. Neurodiversity, 4. https://doi.org/10.1177/27546330261437265

Publication date: 1 Mar 2026 Added to AutiHub: 25 Sep 2026 Type: Article Article language: English
Publisher source (DOI) OpenAlex source

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Authors

Publication authors
7
Publication authors identified as autistic
4 / 7 (57.1%)
  1. Caitlin Hughes *
  2. Chris Wells
  3. Emma Nicholson
  4. Bee Mayhew *
  1. Sheldon Gay
  2. Marni Kammersell *
  3. Teena Mogler *

Abstract

This article introduces podcasting as a methodological advancement within critical neurodiversity studies, positioning it as a form of neuroqueer collaborative autoethnography that enables epistemic healing. Through a collaborative podcast episode featuring seven neurodivergent podcasters, we demonstrate how voice-centered, relational knowledge-making can disrupt traditional academic gatekeeping while affirming neurodivergent ways of knowing. Our approach combines neuroqueer theory's challenge to neuronormative research practices with collaborative autoethnography's emphasis on shared meaning-making, using podcasting as both method and medium. Guided by five open-ended questions rather than rigid scripts, our conversation exemplifies how podcasting can function as epistemic repair by restoring silenced ways of knowing through accessible, community-rooted dialogue. We argue that podcasting offers critical neurodiversity studies a participatory methodology that honors complexity, embraces messiness, and builds community while generating rigorous cultural critique. This work contributes to growing calls for neurodivergent-led research methodologies that serve communities rather than studying them.

Bibliography cited by this reference

Cited references are imported from external metadata sources when they are available. The list may be partial.

Cited bibliography overview

These indicators describe the bibliography cited by this publication. An author name is counted each time it appears in one cited reference, so the same person can be counted more than once. Names not yet linked to an author already present in AutiHub are treated as unknown, not as non-autistic. Last computed: 2 Oct 2026 07:50.

Cited references
29
With a DOI
16
Without a DOI, from raw bibliography text
13
5 / 29 (17.2%) cited references include at least one author identified as autistic.
References with data to complete
7 / 29 (24.1%)
References with detected author names
22 / 29 (75.9%)
Without detected author names
7
Without a structured title
7
Without a stable identifier
12
References with raw author names still to review
6
References with external metadata lookup issues
0
These indicators apply to cited references displayed on this page, after technical duplicates have been merged. A reference without a DOI can still support author statistics when a title and author names are available.
Author names detected in the cited bibliography
41
From DOI or external metadata
41
From validated raw bibliography text
0
Raw names already validated
0
Raw names still to review
6
18 / 41 (43.9%) names are linked to an author already present in AutiHub. 23 / 41 (56.1%) names are not yet linked.
Names linked to a person identified as autistic
13 / 41 (31.7%)
Calculated across all author names detected in the cited bibliography. Among names linked to an author already present in AutiHub: 13 / 18 (72.2%). Distinct people identified as autistic: 10 / 38 (26.3%).
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