Emotional labour and cord blood collection: frontline perspectives
Bibliographic record
Abstract
PURPOSE: This paper aims to examine emotional labour in the work of frontline staff (FLS) of the Canadian Blood Services' Cord Blood Bank (CBB), contributes to understandings of emotional labour by allied healthcare workers and suggests implications for healthcare managers. DESIGN/METHODOLOGY/APPROACH: Qualitative interviews with 15 FLS were conducted and analyzed as part of a process evaluation of donor recruitment and cord blood collection in Canada. FINDINGS: Emotional labour with donors and hospital staff emerged as a vital component of FLS' donor recruitment and cord blood collection work. Emotional labour was performed with donors to contribute to a positive birthing experience, facilitate communication and provide support. Emotional labour was performed with hospital staff to gain acceptance and build relationships, enlist support and navigate hierarchies of authority. RESEARCH LIMITATIONS/IMPLICATIONS: The results indicate that FLS perform emotional labour with women to provide donor care and with hospital staff to facilitate organizational conditions. The findings are based on FLS' accounts of their work and would be enhanced by research that examines the perspectives of donors and hospital staff. PRACTICAL IMPLICATIONS: Attention should be paid to organizational conditions that induce the performance of emotional labour and may add to FLS workload. Formal reciprocal arrangements between FLS and hospital staff may reduce the responsibility on FLS and enable them to focus on recruitment and collections. ORIGINALITY/VALUE: This paper addresses a gap in the healthcare management literature by identifying the emotional labour of allied healthcare workers. It also contributes to the cord blood banking literature by providing empirically grounded analysis of frontline collection staff.
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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.016 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".