Supporting Employees Who Deploy: The Case for Financial Assistance to Employers of Military Reservists.” C.D. Howe Institute Backgrounder 123
Bibliographic record
Abstract
In this issue... Given the key roles Canadian reservists play in meeting Canada's increasing domestic and international security demands, policymakers need to rethink who pays for employer costs when employees deploy. NO. 123, JANUARY 2010 GOVERNANCE AND PUBLIC INSTITUTIONS Military reservists have become a vital component of Canada’s forces at home and abroad, and like their counterparts in the regular forces, provide a service for all Canadians. However, owing to recent federal and provincial job protection legislation, employers of reservists tend to bear a disproportionate share of the costs when their employees are deployed overseas or domestically. If reservists choose to take on full-time military duties, their civilian employer’s search for a temporary replacement worker of equal skill represents a genuine and potentially significant cost. An unintended consequence of the current policy framework is that relationships among employers, reservist employees, and the military can be eroded. Canadian employers of reservists and the Canadian Forces need to work together to restore and strengthen that relationship, in combination with policy reforms at the federal level. Given the key roles Canadian reservists play in meeting increasing domestic and international security demands, policymakers need to rethink who pays for employer costs from the temporary loss of an employee and how this, in turn, affects a reservist’s smooth transition away from – and back to – civilian life. This Backgrounder urges financial assistance for employers who incur costs by protecting the jobs of reservists who choose to serve full-time in the military. Such a program would target the provision of higher levels of benefits to firms likely to suffer disproportionately from the loss of an employee, therefore shifting the costs of some military operations from a few employers to all taxpayers, but at a low price. A Canadian system of financial assistance for employers would more equitably distribute the costs of national defence actions that benefit all Canadians, and be fair to the general public. ABOUT THE INSTITUTE
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.005 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.040 | 0.031 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".