Canadian ROI Task Group Measuring and Reporting Fundraising Costs: A Canadian Perspective Executive Summary
Bibliographic record
Abstract
There is great public interest in charitable organization’s fundraising costs. Reports on costs tend to focus on cost ratios (fundraising costs as a percentage of funds raised). Critics contend that reporting cost ratios is too simplistic to be meaningful in comparing organizations that may have very different circumstances. Nonprofit board members and administrators have a responsibility to 1) ensure that their organization’s return on investment (ROI) in fundraising is reasonable through good internal management practices, and 2) communicate to their constituents and the general public that fundraising is an investment in achieving the goals, objectives and anticipated outcomes described in the organization’s strategic plan. Guidelines for ROI decision making include: 1) Measure fundraising expenses, number of gifts and amount of gifts by fundraising activity and calculate the return on investment for each activity each year. 2) Determine priorities for resource allocation based the outcomes envisioned in your organization’s strategic plan. 3) Calculate fundraising costs and revenues using rolling averages over a period of three to
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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 | 0.027 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".