Emotion regulation as affective neoliberal governmentality
Bibliographic record
Abstract
Emotion regulation is central in many therapy models, including couple and family therapy models. This article draws on poststructuralist governmentality studies and processual affect theory to offer insight into how the therapeutic concept of emotion regulation may reflect and support neoliberal affective forms of self-governance. We suggest that couple and family therapy-through using professional discourses and affect-oriented techniques or interventions-may be another site wherein neoliberal governmentality is implemented and extended in contemporary westernized neoliberalized societies. In facilitating emotion regulation, we argue that there is a risk that therapists may implicitly promote a neoliberal worldview that encourages clients to mobilize neoliberal techniques to become self-improving, entrepreneurial subjects, responsible for their happiness and well-being. Conditions of precarity associated with individualist, neoliberal capitalist ideologies and policies (e.g., unemployment, job insecurity, forced migration, wealth inequalities, mass incarceration, social isolation) generate emotional burdens for people to manage that professional techniques or interventions may normalize as clients' self-management tasks. We theorize emotion regulation as an affective governmentality tactic of power and suggest that couple and family therapy can offer points of resistance to individualization and responsibilization and opportunities for creating or affirming alternative subjectivities and affectivities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.033 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".