JOURNAL ARTICLE

A Group Psychoanalytic Approach to the Social Dreaming Matrix: A Found‐and‐Created Device.

  • Published In: British Journal of Psychotherapy, 2023, v. 39, n. 4. P. 732 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Salaam Abdel‐Malek, Hana 3 of 3

Abstract

To differentiate the Social Dreaming Matrix from Group Relations Conferences, Gordon Lawrence provided a specific denomination, framework and primary task. Despite these new parameters, Lawrence understood that group dynamics persisted in the Matrix, perceiving social dreaming and group dynamics as two lenses of a binocular informing the Matrix. However, to fulfil the Matrix's primary task of accessing the social unconscious, he advocated a non‐psychoanalytic monocular vision emphasizing social dreaming. In this article, I argue that the Social Dreaming Matrix and the Dream Reflection Dialogue that follows are, from a psychoanalytic perspective, two moments of a group whose primary task is Social Dreaming. Looking from a psychoanalytic perspective through the two lenses of social dreaming and group dynamics provides a wider perspective of the social unconscious, generating insights. This group psychoanalytic approach is a found‐and‐created framework rediscovering and recreating the object‐Social Dreaming Matrix framework proposed by Lawrence. To support this argument, I analysed a series of Social Dreaming Matrixes and Dream Reflection Dialogues occurring during a social dreaming training programme to show how the unfolding group dynamics revealed the social unconscious as did social dreaming. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:British Journal of Psychotherapy. 2023/11, Vol. 39, Issue 4, p732
  • Document Type:Article
  • Subject Area:Literature and Writing
  • Publication Date:2023
  • ISSN:0265-9883
  • DOI:10.1111/bjp.12862
  • Accession Number:172960023
  • Copyright Statement:Copyright of British Journal of Psychotherapy is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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