Stigmatized (M)Others: Navigating Stigma, Sex Work, and Motherhood in Canada
Bibliographic record
Abstract
Despite a large body of research exploring the obstacles sex workers face due to their occupational stigma, little research focuses on how their stigmatized paid work influences their navigation of unpaid care, especially in the context of the COVID-19 pandemic. My dissertation examines the narrated and photographic experiences of womxn in Canada who identify as both mothers and sex workers and asks: how do these womxn navigate and negotiate the daily work of unwaged social reproduction and paid work in stigmatized and precarious conditions? This dissertation is informed by feminist methodologies, visual methodologies, and contributes to literatures on stigma, sex work stigma, social reproduction, unpaid care work, mothering, and working motherhood. Fourteen participants in this qualitative project engaged in autophotography, capturing their daily routines and surroundings to provide visual insight into their daily lives. Then each participant attended a photo elicitation interview to discuss the meanings, experiences, and feelings being conveyed in their selected photographs. My findings illuminate that sex work stigma operates contextually, influencing these mothers’ engagement with and disclosure of their stigmatized paid work, their families’ experiences with courtesy stigma, and the structural barriers they face as sex working mothers. This dissertation also explores participants’ engagement with mothering practices, crediting their ability to be good, empathetic mothers because of their experiences navigating stigmatic occupations and their transferrable skills as sex workers. Womxn’s choices to navigate sex work and mothering are acknowledged as being both calculated and meaningful— granting sex workers financial security, flexible working hours, and unique opportunities to invest time into themselves and their families. To uphold the aims of producing accessible research, these images were displayed in public fundraising exhibits, relying on participant observation and anonymous feedback to further assess the project’s ability to co-produce destigmatizing and empathetic knowledges—by, with and for sex workers. All funds raised from these exhibits were donated to various sex worker grassroots organizations in Canada to assist in funding their ongoing mutual aid efforts and to ensure this research possess tangible benefits for sex workers themselves.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.035 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".