Reducing pain into a tablet substantiating and numbing race-based mental health during the COVID-19 pandemic
Bibliographic record
Abstract
The COVID-19 pandemic may have had many negative consequences, and yet a lot was left in its wake that could help shape mental health discussions in health care settings in Canada. This paper is shaped by stories told by Filipino nurses working in Northern Ontario. While there is a plethora of studies looking at mental health issues among nurses and other health care professionals in Canadian hospitals, a gap still remains in regard to the experiences of nurses and health care workers in Northern Ontario during COVID-19. This study seeks to look at the differentiated experiences of mental health among health care professionals during and after COVID-19. This qualitative study employs a narrative approach to discuss how neoliberal capitalism, gendered racism, substance use and colonialism shaped mental health outcomes among Filipino health care workers. While many studies have focused on mental health issues among health care providers, there has been minimal focus on race-based trauma and the ways in which substance use is employed to reduce mental health issues to an individual issue, leaving pharmaceutical companies free to boost their profits. This paper employs intersectional analysis to argue for a more comprehensive understanding of mental health issues among health care workers and allow an understanding of a culturally informed perspective to inform health care policies. The result to the study depicts the various forms of race-based trauma faced by Filipino health care workers and the use of over-the-counter medication to navigate themselves through the health care system. Note that the paper will employ the term healthcare workers and nurses interchangeably.
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How this classification was reachedexpand
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 | 0.012 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".