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Record W2887608362 · doi:10.1177/0840470418794209

Should influenza vaccination be mandatory for healthcare workers?

2018· article· en· W2887608362 on OpenAlexaff
Nikolija Lukich, Michael Kekewich, Virginia Roth

Bibliographic record

VenueHealthcare Management Forum · 2018
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsAutonomyVaccinationHealth careImmunizationOrder (exchange)Work (physics)Healthcare workerPublic relationsPublic healthMedicinePerspective (graphical)BusinessNursingPolitical scienceLawImmunology

Abstract

fetched live from OpenAlex

Each year, many healthcare organizations deal with low influenza immunization rates among staff. Mandatory influenza vaccination programs may be considered in order to address this issue. These types of programs have caused controversy in the past, as staff has argued that they infringe upon their liberties and right to autonomy. However, if viewed from a public health perspective, mandatory vaccination programs are beneficial for both employees and patients and can be justified. When individuals make the decision to work in the medical field, it is assumed that their values align with those of the organization for which they work. This overrides their right to autonomy, since they are expected to put the safety of their patients ahead of their own personal interests. Although some may argue that receiving a flu shot is unsafe, evidence has demonstrated the opposite, and the minimal discomfort that may result from a vaccine is not enough to negate the responsibilities that healthcare workers have toward the patients they serve.

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 imitation

Not 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.

metaresearch head score (Codex)0.022
metaresearch head score (Gemma)0.102
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.024
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.102
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0040.008
Scholarly communication0.0030.006
Open science0.0010.003
Research integrity0.0240.015
Insufficient payload (model declined to judge)0.0040.002

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 head0.211
GPT teacher head0.541
Teacher spread0.330 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations8
Published2018
Admission routes1
Has abstractyes

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