Power Narrativized: How Temporality and Emotionality Empower Activist Identity Construction
Bibliographic record
Abstract
To better understand the role of power in identity construction, we ask how workers construct a labour activist identity based on their experience of disempowerment. In examining labour activists’ accounts, central to their identity construction, we find two sets of power-infused narratives of their experienced disempowerment embedded in a temporal framework (i.e., past, present, and future). For some, their past experience with disempowerment in families internalizes a sense of powerlessness and unionism is seen as a tool to overcome this; we term this episodic power narrative as it reflects a self-focused process in which they obtain a personal sense of growing influence by participating in unionism. For others, their present experience with disempowerment in employment features a realization about the power asymmetry in the employment system and unionism is seen as an institution to counter this; we term this systemic power narrative as it highlights a collective-focused process that is more about leveraging activism to join an institutionalized power struggle. We also find a narrative of felt disempowerment featuring a multiplicity of ambivalent emotions, from which a ‘deep story’ emerges and speaks to a broader power story around class struggles in the society. Taken together, we offer a conceptual perspective to understanding the power-identity relationship different from existing perspectives, such as identity work and emancipation. We also contribute more generally to the growing literature showing the importance of temporality and emotionality to identity processes.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.019 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".