health_workers (profession)

literal strings: health workers, Health Workers, Health workers

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• health_workers is a profession     
• health_workers is a profession that is a kind of nurses (jobposition)     
• nurses is a profession that is a kind of health_workers (profession)     

categories

• profession(100.0%)
• MBL @196 (98.4%) on 04-feb-2011 [ Promotion of profession:health_workers professionistypeofprofession jobposition:nurses ]
• CMC @538 (100.0%) on 24-mar-2012 [ CHARS 4.23495 LASTSUFFIX=rs 2.12149 SUFFIX=ers 1.91302 LASTSUFFIX=ers 1.87020 SUFFIX=rs 1.83606 PREFIX=hea 1.81482 FULL_POS=NN_NNS 1.11349 POS=NNS -0.99394 SHORT_WORDSHAPE=Aa -1.67647 WORDS -9.20382 ] using health_workers
• SEAL @856 (61.4%) on 20-jul-2014 [ 1 ] using health_workers
• LE @1099 (99.7%) on 23-jan-2018

relations

• professionistypeofprofession
• nurses (jobposition) (98.4%)
• CPL @1094 (98.4%) on 01-jan-2018 [ "arg1 including Registered arg2" "arg1 such as nurses and arg2" "arg1 such as physicians and arg2" "arg1 such as doctors and arg2" "arg1 including doctors and arg2" "arg1 such as registered arg2" ] using (health_workers, nurses)
• professiontypehasprofession
• nurses (jobposition) (100.0%)
• OE @803 (100.0%) on 13-jan-2014 [   ] using (nurses, health_workers)
• CPL @1098 (99.2%) on 21-jan-2018 [ "arg2 including Registered arg1" "arg2 such as nurses and arg1" "arg2 such as physicians and arg1" "arg2 such as doctors and arg1" "arg2 including doctors and arg1" "arg2 include registered arg1" "arg2 such as registered arg1" ] using (nurses, health_workers)

NELL has only weak evidence for items listed in grey

• professionistypeofprofession
• midwives (profession)
• CPL @1097 (75.0%) on 19-jan-2018 [ "arg1 like nurses and arg2" "arg1 such as doctors and arg2" ] using (health_workers, midwives)
• physician_assistants
• CPL @1099 (50.0%) on 23-jan-2018 [ "arg1 like nurses and arg2" ] using (health_workers, physician_assistants)
• servants (profession)
• CPL @1116 (75.0%) on 06-sep-2018 [ "arg2 such as teachers and arg1" "arg2 like teachers and arg1" ] using (health_workers, servants)
• workers (profession)
• CPL @1097 (87.5%) on 19-jan-2018 [ "arg1 and other allied health arg2" "arg1 and other health arg2" "arg1 and allied health arg2" ] using (health_workers, workers)
• professiontypehasprofession
• midwives (profession)
• CPL @1109 (75.0%) on 12-jun-2018 [ "arg2 like nurses and arg1" "arg2 such as doctors and arg1" ] using (midwives, health_workers)
• professionistypeofprofession
• women (agent)
• CPL @1116 (75.0%) on 06-sep-2018 [ "arg2 and doctors and other arg1" "arg2 were trained as arg1" ] using (health_workers, women)
• nurses (boardgame)
• CPL @1094 (98.4%) on 01-jan-2018 [ "arg1 including Registered arg2" "arg1 such as nurses and arg2" "arg1 such as physicians and arg2" "arg1 such as doctors and arg2" "arg1 including doctors and arg2" "arg1 such as registered arg2" ] using (health_workers, nurses)
• midwives (book)
• CPL @1097 (75.0%) on 19-jan-2018 [ "arg1 like nurses and arg2" "arg1 such as doctors and arg2" ] using (health_workers, midwives)
• women (book)
• CPL @1116 (75.0%) on 06-sep-2018 [ "arg2 and doctors and other arg1" "arg2 were trained as arg1" ] using (health_workers, women)
• women (celltype)
• CPL @1116 (75.0%) on 06-sep-2018 [ "arg2 and doctors and other arg1" "arg2 were trained as arg1" ] using (health_workers, women)
• women (clothing)
• CPL @1116 (75.0%) on 06-sep-2018 [ "arg2 and doctors and other arg1" "arg2 were trained as arg1" ] using (health_workers, women)
• workers (geopoliticallocation)
• CPL @1097 (87.5%) on 19-jan-2018 [ "arg1 and other allied health arg2" "arg1 and other health arg2" "arg1 and allied health arg2" ] using (health_workers, workers)
• people
• CPL @1105 (87.5%) on 25-mar-2018 [ "arg2 were trained as arg1" "arg2 such as teachers and arg1" "arg2 like teachers and arg1" ] using (health_workers, people)
• women (magazine)
• CPL @1116 (75.0%) on 06-sep-2018 [ "arg2 and doctors and other arg1" "arg2 were trained as arg1" ] using (health_workers, women)
• servants (male)
• CPL @1116 (75.0%) on 06-sep-2018 [ "arg2 such as teachers and arg1" "arg2 like teachers and arg1" ] using (health_workers, servants)
• women (male)
• CPL @1116 (75.0%) on 06-sep-2018 [ "arg2 and doctors and other arg1" "arg2 were trained as arg1" ] using (health_workers, women)
• nurses (medicalprocedure)
• CPL @1094 (98.4%) on 01-jan-2018 [ "arg1 including Registered arg2" "arg1 such as nurses and arg2" "arg1 such as physicians and arg2" "arg1 such as doctors and arg2" "arg1 including doctors and arg2" "arg1 such as registered arg2" ] using (health_workers, nurses)
• women (mldataset)
• CPL @1116 (75.0%) on 06-sep-2018 [ "arg2 and doctors and other arg1" "arg2 were trained as arg1" ] using (health_workers, women)
• women (nondiseasecondition)
• CPL @1116 (75.0%) on 06-sep-2018 [ "arg2 and doctors and other arg1" "arg2 were trained as arg1" ] using (health_workers, women)
• workers (person)
• CPL @1097 (87.5%) on 19-jan-2018 [ "arg1 and other allied health arg2" "arg1 and other health arg2" "arg1 and allied health arg2" ] using (health_workers, workers)
• women (personalcareitem)
• CPL @1116 (75.0%) on 06-sep-2018 [ "arg2 and doctors and other arg1" "arg2 were trained as arg1" ] using (health_workers, women)
• women (personus)
• CPL @1116 (75.0%) on 06-sep-2018 [ "arg2 and doctors and other arg1" "arg2 were trained as arg1" ] using (health_workers, women)
• women (physicalaction)
• CPL @1116 (75.0%) on 06-sep-2018 [ "arg2 and doctors and other arg1" "arg2 were trained as arg1" ] using (health_workers, women)
• servants (politicsissue)
• CPL @1116 (75.0%) on 06-sep-2018 [ "arg2 such as teachers and arg1" "arg2 like teachers and arg1" ] using (health_workers, servants)
• workers (politicsissue)
• CPL @1097 (87.5%) on 19-jan-2018 [ "arg1 and other allied health arg2" "arg1 and other health arg2" "arg1 and allied health arg2" ] using (health_workers, workers)
• professionals
• CPL @1094 (100.0%) on 01-jan-2018 [ "arg1 and other health arg2" "arg1 and all health arg2" "arg1 and nurses and other arg2" "arg1 and other allied health arg2" "arg1 and other helping arg2" "arg1 and other primary health care arg2" "arg1 and other trained arg2" "arg1 and other healthcare arg2" "arg1 and allied healthcare arg2" "arg1 or other health care arg2" "arg1 and allied health arg2" ] using (health_workers, professionals)
• OE @1113 (93.0%) on 02-aug-2018 [ https://collegegrad.com/careers/health-educators-and-community-health-workers https://www.ncbi.nlm.nih.gov/pubmed/9247828 https://collegegrad.com/careers/health-educators-and-community-health-workers http://1millionhealthworkers.org/data-for-decision-making/ https://medicine.wright.edu/pediatrics/center-for-healthy-communities/ohio-community-health-workers-association https://en.wikipedia.org/wiki/Health_professional  ] using (health_workers, professionals)
• women (sportsgame)
• CPL @1116 (75.0%) on 06-sep-2018 [ "arg2 and doctors and other arg1" "arg2 were trained as arg1" ] using (health_workers, women)
• women (sportsleague)
• CPL @1116 (75.0%) on 06-sep-2018 [ "arg2 and doctors and other arg1" "arg2 were trained as arg1" ] using (health_workers, women)
• workers (tradeunion)
• CPL @1097 (87.5%) on 19-jan-2018 [ "arg1 and other allied health arg2" "arg1 and other health arg2" "arg1 and allied health arg2" ] using (health_workers, workers)
• women (university)
• CPL @1116 (75.0%) on 06-sep-2018 [ "arg2 and doctors and other arg1" "arg2 were trained as arg1" ] using (health_workers, women)
• workers (vehicle)
• CPL @1097 (87.5%) on 19-jan-2018 [ "arg1 and other allied health arg2" "arg1 and other health arg2" "arg1 and allied health arg2" ] using (health_workers, workers)
• midwives (victim)
• CPL @1097 (75.0%) on 19-jan-2018 [ "arg1 like nurses and arg2" "arg1 such as doctors and arg2" ] using (health_workers, midwives)
• women (visualartmovement)
• CPL @1116 (75.0%) on 06-sep-2018 [ "arg2 and doctors and other arg1" "arg2 were trained as arg1" ] using (health_workers, women)