COVID-19 Policies’ Impact on House Cleaners’ Workplace Precarity Article Swipe
Kara Johansen
,
Alexa Setteducate
,
Maggi Price
,
David L. Blustein
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.31219/osf.io/vs57d_v1
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.31219/osf.io/vs57d_v1
The COVID-19 pandemic increased the volume of precarious work (i.e. work that is unstable, often without social/legal protections) across many industries, including for domestic workers. House cleaners face particularly precarious conditions due to being predominantly marginalized (i.e. lower socio-economic status, racial/ethnic minorities, non-native English speakers) women, often with informal contracts. The present grounded-theory qualitative study elucidates how COVID-19 policies in two different US cities (Boston, MA and Dallas, TX) affected precarity in house cleaners’ work. Dallas had far less strict COVID-19 policies (e.g., shorter mask mandates and quicker business re-openings) compared to Boston. In each city, house cleaners (n=10 in Dallas and n=8 in Boston) participated in 15-35 minute semi-structured interviews over Zoom or phone. Participants were asked about their working relationships during COVID-19, as well as how they coped with health safety and payments. House cleaners reported that the COVID-19 increased the precarity of their work in three essential ways: (1) furloughs and firings without protections (2) duress around their health and safety while at work, and (3) increased awareness of existing power structures in their employer-employee relationships. However, Dallas house cleaners reported shorter furloughs, higher rates of discomfort around safety, and more instances of a new awareness in power structures than their Boston counterparts, demonstrating differences in precarity based on local COVID-19 policies and employer attitudes. Importantly, precarity in work can result in negative psychological outcomes such as anxiety and depression and a lack of dignity.
Related Topics
Concepts
Precarity
Coronavirus disease 2019 (COVID-19)
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
2019-20 coronavirus outbreak
Business
Virology
Economics
Medicine
Outbreak
Market economy
Disease
Pathology
Infectious disease (medical specialty)
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.31219/osf.io/vs57d_v1
- OA Status
- gold
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4408360633
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4408360633Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.31219/osf.io/vs57d_v1Digital Object Identifier
- Title
-
COVID-19 Policies’ Impact on House Cleaners’ Workplace PrecarityWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-01-12Full publication date if available
- Authors
-
Kara Johansen, Alexa Setteducate, Maggi Price, David L. BlusteinList of authors in order
- Landing page
-
https://doi.org/10.31219/osf.io/vs57d_v1Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.31219/osf.io/vs57d_v1Direct OA link when available
- Concepts
-
Precarity, Coronavirus disease 2019 (COVID-19), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), 2019-20 coronavirus outbreak, Business, Virology, Economics, Medicine, Outbreak, Market economy, Disease, Pathology, Infectious disease (medical specialty)Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4408360633 |
|---|---|
| doi | https://doi.org/10.31219/osf.io/vs57d_v1 |
| ids.doi | https://doi.org/10.31219/osf.io/vs57d_v1 |
| ids.openalex | https://openalex.org/W4408360633 |
| fwci | |
| type | preprint |
| title | COVID-19 Policies’ Impact on House Cleaners’ Workplace Precarity |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T11711 |
| topics[0].field.id | https://openalex.org/fields/20 |
| topics[0].field.display_name | Economics, Econometrics and Finance |
| topics[0].score | 0.4036000072956085 |
| topics[0].domain.id | https://openalex.org/domains/2 |
| topics[0].domain.display_name | Social Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2002 |
| topics[0].subfield.display_name | Economics and Econometrics |
| topics[0].display_name | COVID-19 Pandemic Impacts |
| topics[1].id | https://openalex.org/T11959 |
| topics[1].field.id | https://openalex.org/fields/36 |
| topics[1].field.display_name | Health Professions |
| topics[1].score | 0.38999998569488525 |
| topics[1].domain.id | https://openalex.org/domains/4 |
| topics[1].domain.display_name | Health Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/3600 |
| topics[1].subfield.display_name | General Health Professions |
| topics[1].display_name | Employment and Welfare Studies |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C2778071103 |
| concepts[0].level | 2 |
| concepts[0].score | 0.899571418762207 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q15404623 |
| concepts[0].display_name | Precarity |
| concepts[1].id | https://openalex.org/C3008058167 |
| concepts[1].level | 4 |
| concepts[1].score | 0.8326488733291626 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q84263196 |
| concepts[1].display_name | Coronavirus disease 2019 (COVID-19) |
| concepts[2].id | https://openalex.org/C3007834351 |
| concepts[2].level | 5 |
| concepts[2].score | 0.5359094738960266 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q82069695 |
| concepts[2].display_name | Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) |
| concepts[3].id | https://openalex.org/C3006700255 |
| concepts[3].level | 3 |
| concepts[3].score | 0.532087504863739 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q81068910 |
| concepts[3].display_name | 2019-20 coronavirus outbreak |
| concepts[4].id | https://openalex.org/C144133560 |
| concepts[4].level | 0 |
| concepts[4].score | 0.4056524634361267 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q4830453 |
| concepts[4].display_name | Business |
| concepts[5].id | https://openalex.org/C159047783 |
| concepts[5].level | 1 |
| concepts[5].score | 0.26409101486206055 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q7215 |
| concepts[5].display_name | Virology |
| concepts[6].id | https://openalex.org/C162324750 |
| concepts[6].level | 0 |
| concepts[6].score | 0.24417605996131897 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q8134 |
| concepts[6].display_name | Economics |
| concepts[7].id | https://openalex.org/C71924100 |
| concepts[7].level | 0 |
| concepts[7].score | 0.21971580386161804 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q11190 |
| concepts[7].display_name | Medicine |
| concepts[8].id | https://openalex.org/C116675565 |
| concepts[8].level | 2 |
| concepts[8].score | 0.07151111960411072 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q3241045 |
| concepts[8].display_name | Outbreak |
| concepts[9].id | https://openalex.org/C34447519 |
| concepts[9].level | 1 |
| concepts[9].score | 0.06471920013427734 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q179522 |
| concepts[9].display_name | Market economy |
| concepts[10].id | https://openalex.org/C2779134260 |
| concepts[10].level | 2 |
| concepts[10].score | 0.0 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q12136 |
| concepts[10].display_name | Disease |
| concepts[11].id | https://openalex.org/C142724271 |
| concepts[11].level | 1 |
| concepts[11].score | 0.0 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q7208 |
| concepts[11].display_name | Pathology |
| concepts[12].id | https://openalex.org/C524204448 |
| concepts[12].level | 3 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q788926 |
| concepts[12].display_name | Infectious disease (medical specialty) |
| keywords[0].id | https://openalex.org/keywords/precarity |
| keywords[0].score | 0.899571418762207 |
| keywords[0].display_name | Precarity |
| keywords[1].id | https://openalex.org/keywords/coronavirus-disease-2019 |
| keywords[1].score | 0.8326488733291626 |
| keywords[1].display_name | Coronavirus disease 2019 (COVID-19) |
| keywords[2].id | https://openalex.org/keywords/severe-acute-respiratory-syndrome-coronavirus-2 |
| keywords[2].score | 0.5359094738960266 |
| keywords[2].display_name | Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) |
| keywords[3].id | https://openalex.org/keywords/2019-20-coronavirus-outbreak |
| keywords[3].score | 0.532087504863739 |
| keywords[3].display_name | 2019-20 coronavirus outbreak |
| keywords[4].id | https://openalex.org/keywords/business |
| keywords[4].score | 0.4056524634361267 |
| keywords[4].display_name | Business |
| keywords[5].id | https://openalex.org/keywords/virology |
| keywords[5].score | 0.26409101486206055 |
| keywords[5].display_name | Virology |
| keywords[6].id | https://openalex.org/keywords/economics |
| keywords[6].score | 0.24417605996131897 |
| keywords[6].display_name | Economics |
| keywords[7].id | https://openalex.org/keywords/medicine |
| keywords[7].score | 0.21971580386161804 |
| keywords[7].display_name | Medicine |
| keywords[8].id | https://openalex.org/keywords/outbreak |
| keywords[8].score | 0.07151111960411072 |
| keywords[8].display_name | Outbreak |
| keywords[9].id | https://openalex.org/keywords/market-economy |
| keywords[9].score | 0.06471920013427734 |
| keywords[9].display_name | Market economy |
| language | en |
| locations[0].id | doi:10.31219/osf.io/vs57d_v1 |
| locations[0].is_oa | True |
| locations[0].source | |
| locations[0].license | public-domain |
| locations[0].pdf_url | |
| locations[0].version | acceptedVersion |
| locations[0].raw_type | posted-content |
| locations[0].license_id | https://openalex.org/licenses/public-domain |
| locations[0].is_accepted | True |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | https://doi.org/10.31219/osf.io/vs57d_v1 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5030489370 |
| authorships[0].author.orcid | https://orcid.org/0009-0009-7782-7472 |
| authorships[0].author.display_name | Kara Johansen |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Kara Johansen |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5082801994 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | Alexa Setteducate |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Alexa Setteducate |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5010249064 |
| authorships[2].author.orcid | https://orcid.org/0000-0001-9825-6925 |
| authorships[2].author.display_name | Maggi Price |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Maggi Price |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5038379078 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-4097-0314 |
| authorships[3].author.display_name | David L. Blustein |
| authorships[3].author_position | last |
| authorships[3].raw_author_name | David L. Blustein |
| authorships[3].is_corresponding | False |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.31219/osf.io/vs57d_v1 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | COVID-19 Policies’ Impact on House Cleaners’ Workplace Precarity |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T11711 |
| primary_topic.field.id | https://openalex.org/fields/20 |
| primary_topic.field.display_name | Economics, Econometrics and Finance |
| primary_topic.score | 0.4036000072956085 |
| primary_topic.domain.id | https://openalex.org/domains/2 |
| primary_topic.domain.display_name | Social Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2002 |
| primary_topic.subfield.display_name | Economics and Econometrics |
| primary_topic.display_name | COVID-19 Pandemic Impacts |
| related_works | https://openalex.org/W3036314732, https://openalex.org/W3009669391, https://openalex.org/W3176864053, https://openalex.org/W4206669628, https://openalex.org/W3171943759, https://openalex.org/W4292098121, https://openalex.org/W3154141118, https://openalex.org/W4388896133, https://openalex.org/W3031607536, https://openalex.org/W4224279380 |
| cited_by_count | 0 |
| locations_count | 1 |
| best_oa_location.id | doi:10.31219/osf.io/vs57d_v1 |
| best_oa_location.is_oa | True |
| best_oa_location.source | |
| best_oa_location.license | public-domain |
| best_oa_location.pdf_url | |
| best_oa_location.version | acceptedVersion |
| best_oa_location.raw_type | posted-content |
| best_oa_location.license_id | https://openalex.org/licenses/public-domain |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | https://doi.org/10.31219/osf.io/vs57d_v1 |
| primary_location.id | doi:10.31219/osf.io/vs57d_v1 |
| primary_location.is_oa | True |
| primary_location.source | |
| primary_location.license | public-domain |
| primary_location.pdf_url | |
| primary_location.version | acceptedVersion |
| primary_location.raw_type | posted-content |
| primary_location.license_id | https://openalex.org/licenses/public-domain |
| primary_location.is_accepted | True |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | https://doi.org/10.31219/osf.io/vs57d_v1 |
| publication_date | 2023-01-12 |
| publication_year | 2023 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 196, 234 |
| abstract_inverted_index.In | 93 |
| abstract_inverted_index.MA | 65 |
| abstract_inverted_index.US | 62 |
| abstract_inverted_index.as | 124, 126, 229 |
| abstract_inverted_index.at | 165 |
| abstract_inverted_index.in | 59, 71, 99, 103, 106, 147, 175, 199, 208, 220, 224 |
| abstract_inverted_index.is | 12 |
| abstract_inverted_index.of | 6, 144, 171, 188, 195, 236 |
| abstract_inverted_index.on | 211 |
| abstract_inverted_index.or | 113 |
| abstract_inverted_index.to | 32, 91 |
| abstract_inverted_index.(1) | 151 |
| abstract_inverted_index.(2) | 157 |
| abstract_inverted_index.(3) | 168 |
| abstract_inverted_index.TX) | 68 |
| abstract_inverted_index.The | 0, 50 |
| abstract_inverted_index.and | 66, 86, 101, 133, 153, 162, 167, 192, 215, 231, 233 |
| abstract_inverted_index.can | 222 |
| abstract_inverted_index.due | 31 |
| abstract_inverted_index.far | 77 |
| abstract_inverted_index.for | 22 |
| abstract_inverted_index.had | 76 |
| abstract_inverted_index.how | 56, 127 |
| abstract_inverted_index.n=8 | 102 |
| abstract_inverted_index.new | 197 |
| abstract_inverted_index.the | 4, 139, 142 |
| abstract_inverted_index.two | 60 |
| abstract_inverted_index.Zoom | 112 |
| abstract_inverted_index.each | 94 |
| abstract_inverted_index.face | 27 |
| abstract_inverted_index.lack | 235 |
| abstract_inverted_index.less | 78 |
| abstract_inverted_index.many | 19 |
| abstract_inverted_index.mask | 84 |
| abstract_inverted_index.more | 193 |
| abstract_inverted_index.over | 111 |
| abstract_inverted_index.such | 228 |
| abstract_inverted_index.than | 202 |
| abstract_inverted_index.that | 11, 138 |
| abstract_inverted_index.they | 128 |
| abstract_inverted_index.well | 125 |
| abstract_inverted_index.were | 116 |
| abstract_inverted_index.with | 47, 130 |
| abstract_inverted_index.work | 8, 10, 146, 221 |
| abstract_inverted_index.(i.e. | 9, 36 |
| abstract_inverted_index.(n=10 | 98 |
| abstract_inverted_index.15-35 | 107 |
| abstract_inverted_index.House | 25, 135 |
| abstract_inverted_index.about | 118 |
| abstract_inverted_index.asked | 117 |
| abstract_inverted_index.based | 210 |
| abstract_inverted_index.being | 33 |
| abstract_inverted_index.city, | 95 |
| abstract_inverted_index.coped | 129 |
| abstract_inverted_index.house | 72, 96, 181 |
| abstract_inverted_index.local | 212 |
| abstract_inverted_index.lower | 37 |
| abstract_inverted_index.often | 14, 46 |
| abstract_inverted_index.power | 173, 200 |
| abstract_inverted_index.rates | 187 |
| abstract_inverted_index.study | 54 |
| abstract_inverted_index.their | 119, 145, 160, 176, 203 |
| abstract_inverted_index.three | 148 |
| abstract_inverted_index.ways: | 150 |
| abstract_inverted_index.while | 164 |
| abstract_inverted_index.work, | 166 |
| abstract_inverted_index.work. | 74 |
| abstract_inverted_index.(e.g., | 82 |
| abstract_inverted_index.Boston | 204 |
| abstract_inverted_index.Dallas | 75, 100, 180 |
| abstract_inverted_index.across | 18 |
| abstract_inverted_index.around | 159, 190 |
| abstract_inverted_index.cities | 63 |
| abstract_inverted_index.duress | 158 |
| abstract_inverted_index.during | 122 |
| abstract_inverted_index.health | 131, 161 |
| abstract_inverted_index.higher | 186 |
| abstract_inverted_index.minute | 108 |
| abstract_inverted_index.phone. | 114 |
| abstract_inverted_index.result | 223 |
| abstract_inverted_index.safety | 132, 163 |
| abstract_inverted_index.strict | 79 |
| abstract_inverted_index.volume | 5 |
| abstract_inverted_index.women, | 45 |
| abstract_inverted_index.Boston) | 104 |
| abstract_inverted_index.Boston. | 92 |
| abstract_inverted_index.Dallas, | 67 |
| abstract_inverted_index.English | 43 |
| abstract_inverted_index.anxiety | 230 |
| abstract_inverted_index.firings | 154 |
| abstract_inverted_index.present | 51 |
| abstract_inverted_index.quicker | 87 |
| abstract_inverted_index.safety, | 191 |
| abstract_inverted_index.shorter | 83, 184 |
| abstract_inverted_index.status, | 39 |
| abstract_inverted_index.without | 15, 155 |
| abstract_inverted_index.working | 120 |
| abstract_inverted_index.(Boston, | 64 |
| abstract_inverted_index.COVID-19 | 1, 57, 80, 140, 213 |
| abstract_inverted_index.However, | 179 |
| abstract_inverted_index.affected | 69 |
| abstract_inverted_index.business | 88 |
| abstract_inverted_index.cleaners | 26, 97, 136, 182 |
| abstract_inverted_index.compared | 90 |
| abstract_inverted_index.dignity. | 237 |
| abstract_inverted_index.domestic | 23 |
| abstract_inverted_index.employer | 216 |
| abstract_inverted_index.existing | 172 |
| abstract_inverted_index.informal | 48 |
| abstract_inverted_index.mandates | 85 |
| abstract_inverted_index.negative | 225 |
| abstract_inverted_index.outcomes | 227 |
| abstract_inverted_index.pandemic | 2 |
| abstract_inverted_index.policies | 58, 81, 214 |
| abstract_inverted_index.reported | 137, 183 |
| abstract_inverted_index.workers. | 24 |
| abstract_inverted_index.COVID-19, | 123 |
| abstract_inverted_index.awareness | 170, 198 |
| abstract_inverted_index.different | 61 |
| abstract_inverted_index.essential | 149 |
| abstract_inverted_index.furloughs | 152 |
| abstract_inverted_index.including | 21 |
| abstract_inverted_index.increased | 3, 141, 169 |
| abstract_inverted_index.instances | 194 |
| abstract_inverted_index.payments. | 134 |
| abstract_inverted_index.precarity | 70, 143, 209, 219 |
| abstract_inverted_index.speakers) | 44 |
| abstract_inverted_index.unstable, | 13 |
| abstract_inverted_index.attitudes. | 217 |
| abstract_inverted_index.conditions | 30 |
| abstract_inverted_index.contracts. | 49 |
| abstract_inverted_index.depression | 232 |
| abstract_inverted_index.discomfort | 189 |
| abstract_inverted_index.elucidates | 55 |
| abstract_inverted_index.furloughs, | 185 |
| abstract_inverted_index.interviews | 110 |
| abstract_inverted_index.non-native | 42 |
| abstract_inverted_index.precarious | 7, 29 |
| abstract_inverted_index.structures | 174, 201 |
| abstract_inverted_index.cleaners’ | 73 |
| abstract_inverted_index.differences | 207 |
| abstract_inverted_index.industries, | 20 |
| abstract_inverted_index.minorities, | 41 |
| abstract_inverted_index.protections | 156 |
| abstract_inverted_index.qualitative | 53 |
| abstract_inverted_index.Importantly, | 218 |
| abstract_inverted_index.Participants | 115 |
| abstract_inverted_index.marginalized | 35 |
| abstract_inverted_index.participated | 105 |
| abstract_inverted_index.particularly | 28 |
| abstract_inverted_index.protections) | 17 |
| abstract_inverted_index.re-openings) | 89 |
| abstract_inverted_index.social/legal | 16 |
| abstract_inverted_index.counterparts, | 205 |
| abstract_inverted_index.demonstrating | 206 |
| abstract_inverted_index.predominantly | 34 |
| abstract_inverted_index.psychological | 226 |
| abstract_inverted_index.racial/ethnic | 40 |
| abstract_inverted_index.relationships | 121 |
| abstract_inverted_index.relationships. | 178 |
| abstract_inverted_index.socio-economic | 38 |
| abstract_inverted_index.grounded-theory | 52 |
| abstract_inverted_index.semi-structured | 109 |
| abstract_inverted_index.employer-employee | 177 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.24300902 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |