NOT JUST HOW MANY BUT WHO IS ON SHIFT: THE IMPACT OF WORKPLACE INCIVILITY AND BULLYING AMONG RCAS ON RESIDENT CARE
Bibliographic record
Abstract
Abstract Much of the literature examining the link between care quality and staffing in long-term residential care focuses on staffing ratios and staffing mix; that is, how many staff are on shift. Far less attention has been devoted to exploring the impact of staff members’ workplace relationships, or who is on shift, on care quality. Of increasing concern is the potential for peer incivility and bullying to disrupt the respectful, collaborative and effective working relationships considered key to residential care aides’ (RCAs) care provision. This paper draws on data collected from a critical ethnography examining workplace incivility and bullying in a rural, not-for-profit care home. To date, more than 50 hours of participant observation, and 20 in-depth interviews with RCAs, licensed practical nurses, support staff, management and residents have been conducted. Thematic analyses identified three key themes: impact on resident safety; cutting corners; and impact on resident agitation and anxiety. Impact on resident safety highlights how incivility and bullying can result in non-adherence to two-person lift policies and procedures. Cutting corners outlines how RCAs’ relationships with their co-workers dictates to what extent they provide the requisite care to a resident for whom another RCA is responsible. Impact on resident agitation and anxiety focuses on residents’ reactions to the tensions that emerge between RCAs as a result of incivility and bullying. Findings highlight how peer incivility and bullying may indirectly influence certain quality indicators (e.g., pressure sores, psychotropic medication use) thereby offering additional insight into the staffing-care quality link.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".