Exploring the Experiences of Canadian Autistic Gender Minorities through the Lens of Impression Management
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Both Autistic and non-Autistic individuals engage in Impression Management (IM), a process through which individuals attempt to influence how others perceive them. However, IM appears to have unique characteristics for Autistic individuals (known in the literature as Camouflaging), such as the necessity to suppress Autistic traits, mimic the behaviours, emotions, and expressions of non-autistic peers, and engage in continuous self-monitoring (Cook et al., 2021; Hull et al., 2017; Miller, 2021). Although much research has been conducted, a clear consensus on the definition, measurement, and underlying processes of Autistic camouflaging has yet to be established (Williams, 2021). Ai et al. (2022) aimed to inspire a fresh perspective by connecting the well-established literature on IM with the emerging research on Autistic camouflaging. To accomplish this, they reevaluated Autistic camouflaging, reconceptualizing it as a transactional, context-dependent form of IM. In doing so, they connected the motivations, neurocognitive foundations, and outcomes of camouflaging with the IM framework. Moreover, they proposed that identifying and defining four key components are essential steps in measuring and conceptualizing the mechanisms underlying Autistic camouflaging: (1) Individual skills (executive functions, low uncertainty attunement, monotropism, self-other processing); (2) Motivators (to gain opportunities and rewards OR to reduce stigma and harm); (3) Behaviours (self-presentation, self-concealment, camouflaging, self-monitoring); and (4) Consequences (positive or negative affect, gained or lost opportunities) Our objective is to assess the effectiveness of the IM framework, through secondary data analysis, in capturing the experiences of camouflaging among a small sample of Autistic Women and Non-Binary People in Canada. Additionally, we aim to identify any aspects of the participants' camouflaging experiences that were not addressed by the framework. We will employ the Framework Method to analyze interview data from nine Autistic women and non-binary individuals, utilizing a matrix-based approach for data synthesis. This method allows for systematic data condensation and analysis on a case-by-case and code-by-code basis. Furthermore, we will provide frequency counts to illustrate the prevalence of each component and subcomponent within the IM framework. Should we uncover crucial, previously unexplored (sub)components, or aspects expressed in ways divergent from the IM framework's initial conception, we will propose necessary revisions to enhance its comprehensiveness and accuracy.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.009 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it