Bibliographic record
Abstract
International Journal of Emergency Services (IJES) is publishing thirteen original articles that explore a range of subjects relevant to the three main emergency services (ambulance police and fire).It includes important themes such as mental health and stress patterns, decision-making, use of lights and sirens (L&S), pre-arrival information and support available to emergency medical services (EMS) frontline responders; fatigue and shift pattern in the police; the issue of leadership, informal peer support in the fire services including alcohol and drug related fire injuries and multi-agency collaboration in dealing with underground tunnel incidents.These papers seek to close the information gap by making significant contributions to the emergency management literature and the way we view the role of emergency management practitioners.In our first article, entitled "Mental health patterns during COVID-19 in emergency medical services (EMS)", Silvia Monteiro Fonseca et al. have explored the patterns of EMS personnel's mental health regarding their levels of anxiety, depression and stress during COVID-19 pandemic.The study analyzed over 200 surveys completed by EMS personnel in Portugal, who answered the Patient-Health Questionnaire, Perceived Stress Scale (PSS), COVID-19 Anxiety Scale, Obsessive-Compulsive Inventory, Well-Being Questionnaire and COVID-19-related questions.The study findings explored EMS personnel's patterns of mental health during the COVID-19, as well as its covariates.Results allow to better prepare emergency management, which can develop prevention strategies focused on older professionals, COVID-19-related fears and how personnel assess security measures.Study findings have clear implications for staff working in other domains.Allyson Oliphant et al. in their paper, entitled "At the front of the front-line: Ontario paramedics' experiences of occupational safety, risk and communication during the 2020 COVID-19 pandemic," have explored the impact of the pandemic on a sample of Canadian paramedics.Their study aimed to determine on what bases paramedics in this context have defined themselves as feeling safe or at risk while serving on the front lines role.This qualitative study consisted of semi-structured interviews with primary care paramedics (PCPs), advanced care paramedics (ACPs) and critical care paramedics (CCPs) with first-hand experience responding to the COVID-19 pandemic in Ontario province.The study highlighted several stress factors which are related to personal protective equipment (PPE) and equipment access, risks of infection to self and family, communications and feelings of being systematically under-considered.The study recommendations from this research include, but are not limited to, ensuring a more equitable distribution of protective equipment to paramedics across unevenly funded services and recognizing paramedics face unique and additional stressors in public health emergencies.Ellen Ceklic et al. in their interesting paper, entitled "Can ambulance dispatch categories discriminate traffic incidents that do/do not require a lights and sirens response?",argue that traffic incidents vary considerably in their severity, and the dispatch categories assigned during emergency ambulance calls aim to identify those incidents in greatest need of a L&S response and argue whether dispatch categories could discriminate between those traffic incidents that do/do not require an L&S response.The study was a population-based retrospective cohort study of traffic incidents attended by St John Western Australia (SJ-WA), in Perth, Western Australia.The paper makes a unique contribution as it considers traffic incidents not as a single entity but rather as a number of dispatch categories which has practical implications for those EMS dispatching ambulances to the scene with and the findings have relevance for services in different settings as well.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.042 | 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".