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Record W4376642002 · doi:10.29271/jcpsp.2023.05.590

Mandatory Influenza Immunisation for Healthcare Workers

2023· article· en· W4376642002 on OpenAlexaff
Munazza Saleem

Bibliographic record

VenueJournal of College of Physicians And Surgeons Pakistan · 2023
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsAthabasca University
Fundersnot available
KeywordsVaccinationImmunizationHealth careMedicineInfluenza vaccineNarrative reviewFamily medicineMedical emergencyEnvironmental healthImmunologyIntensive care medicineEconomic growth

Abstract

fetched live from OpenAlex

Healthcare workers (HCWs) are at increased risk of contracting and spreading influenza, especially in annual outbreaks. To achieve a high level of health, this matter can be potentially solved with the implementation of mandatory flu vaccination policies. Despite ample evidence of vaccine effectiveness in reducing sickness, hospital visits, and even deaths, there is resistance to mandatory immunization among HCWs. The purpose of this communication is to present the rationale as to why the influenza vaccine should be mandatory among HCWs and to extract its practical and scholarly significance. The article has been organised to highlight the advantages of immunisation for HCWs, recognise the consequences of non-immunization, and resolve the myths associated with the flu vaccine. Finally, the stance and recommendations of several health agencies around the world on mandating the influenza vaccine for HCWs have been incorporated, with relevant literature evidence consolidated to support the narratives. Key Words: Influenza, Vaccination, Health policy, Healthcare workers' vaccine, Mandatory vaccine.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.063
GPT teacher head0.401
Teacher spread0.338 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2023
Admission routes1
Has abstractyes

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