Evidence map›Paper›PMID 37038431›Full record

ArticleOrganization (London, England)2023

'Anarchist technologies': Anarchism, cybernetics and mutual aid in community responses to the COVID-19 crisis.

Thomas Swann

Open access · bronzeAbstract read
In one paragraph

Article in Organization (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 3 pooled it
12.2field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 3 syntheses or guidelines pooled it, 40 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Observational
  18. Article
  19. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Thomas SwannLoughborough University, UK.ORCID https://orcid.org/0000-0001-9997-6166
Loughborough University · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic that gripped the world since the end of 2019 has been felt most immediately both as a health crisis and an economic, social and political crisis. Secondary impacts of social distancing and lockdown in many countries have put strains on people's capacities to provide essential food and medicines for themselves and their families. In response, outside of centralised government and voluntary sector frameworks, local mutual aid groups have emerged around the world as a primary site of community resilience. Given mutual aid's strong links to the anarchist political tradition, for example in its identification by Kropotkin as a factor in evolution, this article suggests that these new mutual aid groups can be understood best through the related concept of self-organisation. Tying anarchist approaches to mutual aid and self-organisation together, it is argued that cybernetics and Stafford Beer's Viable System Model (VSM) offer useful tools in helping both academic analysis and on-the-ground practice assess and improve the effectiveness of mutual aid in and beyond the COVID-19 crisis. The article offers a qualitative thematic analysis of anarchist and related texts published during the pandemic that reflect on mutual aid practice. In doing so, it highlights some of the challenges and tensions such self-organised mutual aid practice might face and proposes a participatory research agenda drawing on Beer's VSM.

Indexed as

AnarchismCOVID-19cyberneticsmutual aidself-organisation

Identifiers

PMID37038431
PMCPMC10076238
OpenAlexW4225271026

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.