Generic Consulting Contract With Creative Commons License Provision
Bibliographic record
Abstract
LogicalOutcomes, a Canadian nonprofit that develops open source and open access tools for evaluation and monitoring, earns its income through paid consulting projects. Many consulting clients request full and exclusive ownership of any work that is developed during a project funded by them. We believe that this approach to contracting creates barriers to collaboration and sharing. The attached contract template includes a section on proprietary rights that cites Creative Commons licensing of work products. The template may be helpful for other nonprofits and consulting groups who are developing open tools. Proprietary Rights [CLIENT] will have full rights and joint ownership over any templates, reports, or otherwise (collectively hereinafter “Work Products”) produced by LogicalOutcomes as result of or in connection with this Contract and under the terms of the Creative Commons Attribution License 4.0 International, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. To the extent that [CLIENT] provided data is used to create the Work Product, joint ownership shall be construed to mean ownership by [CLIENT] and LogicalOutcomes of the Work Product created by LogicalOutcomes and excluding any [CLIENT] provided data. For the avoidance of doubt, any [CLIENT] data which forms a part of the Work Product created under this Contract, remains the property or licensed property of [CLIENT] and may not be used, transferred, sub-licensed, distributed or reproduced by LogicalOutcomes for any purpose other than the activities in the Statement of Work.
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 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.761 | 0.614 |
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".