Governance and Diversity within the Public Service in Canada: Towards a Viable and Sustainable Representation of Designated Groups (Employment Equity)
Bibliographic record
Abstract
The Canadian Government is constantly seeking to set up thorough-going, responsible administrative practices. Representation is one of the main bases on which the mandate of the federal public service stands. Without this operating principle, a government agency cannot fully and faithfully reflect the concerns of the people it is called to serve. In order to be fair and inclusive, political action must manage diversity on a vast scale, embracing such differences as race, gender, age, language, ethnic origin, religion and disability. Canada’s population is one of the most diversified in the world. Aboriginal peoples and highly varied sustained immigration are just two factors contributing to its diversity and attributes. The political authorities have been totally committed to the question of diversity for several decades. As a consequence, a vast legislative framework has been set up including the 1982 Canadian Charter of Rights and Freedoms. The aim of this article is to introduce the Canadian example with reference to the management of diversity in the public service and, more particularly, the efforts made to achieve fairness in matters of employment. The approach consists first of reviewing the development of the issues of diversity from a general historical and political viewpoint, with special focus on employment equity (ee), and, second, of describing and examining the latest results obtained in terms of representation and its characteristics within the Canadian federal machine. Finally, the importance of identifying challenges for the public service, with a view to responsible governance, is examined within a global discussion of the obstacles identified, the programmes in place and the new approach to be developed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".