Grants and Contributions
About this information
In June 2016, as part of the Open Government Action Plan, the Treasury Board of Canada Secretariat (TBS) committed to increasing the transparency and usefulness of grants and contribution data and subsequently launched the Guidelines on the Reporting of Grants and Contributions Awards, effective April 1, 2018.
The rules and principles governing government grants and contributions are outlined in the Treasury Board Policy on Transfer Payments. Transfer payments are transfers of money, goods, services or assets made from an appropriation to individuals, organizations or other levels of government, without the federal government directly receiving goods or services in return, but which may require the recipient to provide a report or other information subsequent to receiving payment. These expenditures are reported in the Public Accounts of Canada. The major types of transfer payments are grants, contributions and \'other transfer payments\'.
Included in this category, but not to be reported under proactive disclosure of awards, are (1) transfers to other levels of government such as Equalization payments as well as Canada Health and Social Transfer payments. (2) Grants and contributions reallocated or otherwise redistributed by the recipient to third parties; and (3) information that would normally be withheld under the Access to Information Act and the Privacy Act.
$75,000.00
Aug 15, 2023
For-profit organization
Integrated Asset Platform
1009467
The firm's main aim of this project is to explore the potential to completely integrate Asset Management, Filed Service Management and Health & Safety Management under one platform, underpinned by a unified user experience and interface. The firm will leverage AI capabilities to introduce advanced functionalities such as predicting asset failures, forecasting risk factors in field operations, detecting asset defects through photos and videos, analyzing crew capacity and proficiency, and more.
$149,803.00
Apr 1, 2022
For-profit organization
Workplace Risk Identifier & Predictor development
992622
Design a data-lake around all modules within Compliance Science that can measure risk, controls, incidents, and sites. Within this data-lake, apply machine learning to identify variances within assessed risk (frequency, probability, severity) as well as the level of risk mitigation provided by proper controls, in relationship to incidents resulting from risks as well as field/site assessments. The project will help identify if risk is under-estimated, over-estimated or incomplete, as well as factors related to the effectiveness of controls and procedures.