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Part 1: Document Description
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Citation |
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Title: |
Labour Inspection Checklist Dataset |
Identification Number: |
doi:10.18710/7U6TZP |
Distributor: |
DataverseNO |
Date of Distribution: |
2022-10-04 |
Version: |
1 |
Bibliographic Citation: |
Flogard, Eirik Lund, 2022, "Labour Inspection Checklist Dataset", https://doi.org/10.18710/7U6TZP, DataverseNO, V1 |
Citation |
|
Title: |
Labour Inspection Checklist Dataset |
Identification Number: |
doi:10.18710/7U6TZP |
Authoring Entity: |
Flogard, Eirik Lund (NTNU – Norwegian University of Science and Technology) |
Producer: |
Norwegian Labour Inspection Authority |
Distributor: |
DataverseNO |
Distributor: |
NTNU – Norwegian University of Science and Technology |
Access Authority: |
Flogard, Eirik Lund |
Access Authority: |
Mengshoel, Ole Jakob |
Depositor: |
Lund Flogard, Eirik |
Date of Deposit: |
2022-09-29 |
Holdings Information: |
https://doi.org/10.18710/7U6TZP |
Study Scope |
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Keywords: |
Computer and Information Science, Social Sciences, Labour inspection, Checklists, Machine Learning, Non compliance, Long Tail Classification |
Abstract: |
The dataset is intended to use for machine learning to promote United Nations' sustainable development goal 8, target 8: "Protect labour rights and promote safe and secure working environments for all workers, including migrant workers, in particular women migrants, and those in precarious employment". It consists of 63634 instances with past inspections conducted by NLIA between 01/01/2012 and 01/06/2019. Each instance in LICD is described via 575 features and two target variables. Each feature represents either organisational or financial information about the inspected organisation. The first target variable is an identifier for the checklist that were used to inspect the organisation. The variable can be used in a machine learning model to predict the optimal checklist for a specific target organisation. The second target variable denotes whether non-compliance was found at the inspection. The variable can be used to in a machine learning to predict non-compliance to working environment regulations among potential target organisations for inspections. The features, target variables and column names of the dataset have been translated from Norwegian to English. |
Time Period: |
2012-01-01-2019-06-01 |
Country: |
Norway |
Geographic Bounding Box: |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Title: |
Flogard, E. L., & Mengshoel, O. J. (2022). A Dataset for Efforts Towards Achieving the Sustainable Development Goal of Safe Working Environments. Advances in Neural Information Processing Systems, 35, 23297–23310. |
Identification Number: |
https://papers.nips.cc/paper_files/paper/2022/hash/93e4d161bdd93d1dc0202b4044159edb-Abstract-Datasets_and_Benchmarks.html |
Bibliographic Citation: |
Flogard, E. L., & Mengshoel, O. J. (2022). A Dataset for Efforts Towards Achieving the Sustainable Development Goal of Safe Working Environments. Advances in Neural Information Processing Systems, 35, 23297–23310. |
Citation |
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Title: |
Flogard, E. L., & Mengshoel, O. J. (2022, June 29). A Dataset for Efforts Towards Achieving the Sustainable Development Goal of Safe Working Environments. Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track. https://openreview.net/forum?id=93cqcWFpTex |
Identification Number: |
https://openreview.net/forum?id=93cqcWFpTex |
Bibliographic Citation: |
Flogard, E. L., & Mengshoel, O. J. (2022, June 29). A Dataset for Efforts Towards Achieving the Sustainable Development Goal of Safe Working Environments. Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track. https://openreview.net/forum?id=93cqcWFpTex |
Label: |
00Readme.txt |
Text: |
Readme file for the dataset. |
Notes: |
text/plain |
Label: |
Dataset documentation.pdf |
Text: |
Documentation of the dataset in PDF/A format, based on the Datasheets for Datasets framework. |
Notes: |
application/pdf |
Label: |
LICD.csv |
Text: |
Labour Inspection Checklist Dataset |
Notes: |
text/csv |