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.
$236,995.00
Mar 14, 2025
Not-for-profit organization or charity
600073050
600073050
Construction work: The project aims to improve the services offered by an organization responsible for managing a marina.
$1,000,000.00
Mar 14, 2025
For-profit organization
600072996
600072996
Acquisition of equipment and expansion of facilities: The project involves the acquisition of digital production equipment and the acquisition and expansion of a building by a company in the metal processing sector.
$28,200.00
Mar 14, 2025
Indigenous recipients
ISCF-178.1 - ACFN - TORs and Workplan Support 2025
9100015183
The purpose of this funding is to support ACFN with the Terms of Reference and Workplan activities scheduled for the 2025 calendar year.
$28,200.00
Mar 14, 2025
Indigenous recipients
C- ISCF-178.1- ACFN ToR and Workplan 2025-26
9100015183
The purpose of this funding is to support ACFN with the Terms of Reference and Workplan activities scheduled for the 2025 calendar year.
$19,300.00
Mar 14, 2025
Strategic Planning, Training and Equipment
13534474
This project will build and demonstrate increased collaboration with community partners and develop processes, policies and guidance for the Yellowknife Community Justice program, and provide training and equipment.
$43,850.00
Mar 14, 2025
Indigenous recipients
ASSIST Training and Equipment upgrade
13532974
This funding will support attending an ASIST training and an equipment upgrade.
$29,790.00
Mar 14, 2025
Indigenous recipients
Equipment upgrade
13534043
This funding will support the purchase of electronic equipment and furniture for different Indigenous Friendship Centres in Ontario.
$49,900.00
Mar 14, 2025
Indigenous recipients
Siksika Nation Community Engagement
13534250
This project will support increased partnerships and communication about the Siksika justice program, as well as provide cultural learning for clients.
$400,000.00
Mar 14, 2025
Peacemaking Within the Six Nations Territory
13534486
This project will research Six Nations traditional and customary legal practices, develop a peacemaking framework, and develop Indigenous laws. The project will create a Six Nations Peacemaking System framework, laws and policies based on the Six Nations traditional clan systems.
$138,416.00
Mar 14, 2025
Academia
Neuro-Symbolic Probability
1027845
Probability theory is a framework for representing uncertainty – due either to variability or unmodelled, unobserved factors – in a multitude of observed quantities. Probabilistic modeling enables robustness to noise and uncertainty in a number of autonomous systems, and through the widespread adoption of probabilistic algorithms. Probabilistic modeling was responsible for robotics transitioning from fragile, hand-tuned systems, to systems that are robust to operating in the natural world with noisy sensors. In order to interact with a complex and not-perfectly-known environment, both robots and biological creatures need to represent and manipulate probabilities. While probability-based mathematical formalisms such as Bayesian Optimization exist, they often assume an unlimited amount of computing power, and it is unclear how they can be mapped into more realistic physical hardware, or into artificial neural networks. In recent years, a variety of methods have been developed to start to connect probabilistic information with neural networks. The overall goal of the project is to further develop these techniques and to apply them to the flexible soft-robotics systems