Labour Inspection Checklist Dataset (doi:10.18710/7U6TZP)

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Labour Inspection Checklist Dataset

doi:10.18710/7U6TZP

DataverseNO

2022-10-04

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Flogard, Eirik Lund, 2022, "Labour Inspection Checklist Dataset", https://doi.org/10.18710/7U6TZP, DataverseNO, V1

Labour Inspection Checklist Dataset

doi:10.18710/7U6TZP

Flogard, Eirik Lund (NTNU – Norwegian University of Science and Technology)

Norwegian Labour Inspection Authority

DataverseNO

NTNU – Norwegian University of Science and Technology

Flogard, Eirik Lund

Mengshoel, Ole Jakob

Lund Flogard, Eirik

2022-09-29

https://doi.org/10.18710/7U6TZP

Computer and Information Science, Social Sciences, Labour inspection, Checklists, Machine Learning, Non compliance, Long Tail Classification

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.

2012-01-01-2019-06-01

Norway

• West Bounding Longitude: 4.09
• East Bounding Longitude: 31.76
• South Bounding Latitude: 57.76
• North Bounding Latitude: 71.38

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.

https://papers.nips.cc/paper_files/paper/2022/hash/93e4d161bdd93d1dc0202b4044159edb-Abstract-Datasets_and_Benchmarks.html

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.

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

https://openreview.net/forum?id=93cqcWFpTex

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

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00Readme.txt

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Readme file for the dataset.

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Dataset documentation.pdf

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Documentation of the dataset in PDF/A format, based on the Datasheets for Datasets framework.

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LICD.csv

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Labour Inspection Checklist Dataset

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