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.
$15,000.00
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FR-20688
Develop digital adoption plan
$1,000,000.00
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1000973
1000973
To accelerate commercialization and adoption of artificial intelligence software that will improve climate readiness.
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Automation of public disclosure document classification and scoring using PDF text extraction and Natural Language Processing
969042
This project is looking to automate the classification and scoring of publicly traded companies' disclosures using Natural Language Processing (NLP) models. We are looking to classify pages as either positive or negative samples in order to reduce the number of pages reviewed by at least 50% while retaining at least 95% of positive samples. We are also looking to automate scoring of public disclosure documents relative to a framework with a set of specific criteria. Both objectives involve PDF text extraction and NLP as well as comprehensive data gathering and cleaning.