D8.1 - Implementation report on support for "early adopters" and training interventions
Bibliographic record
Abstract
The FIDELIS Repository Training and Support Pillar is responsible for developing and delivering a comprehensive programme of support types which address the needs of the repository community regarding trustworthiness skills. This report details the activities of the first year of the project and how these will inform the upcoming activities in the next years. The training and support programme consists of three different support types: Support for the Adoption of Solutions: A mix of financial support and expert guidance will support repositories to implement and adopt good practices, tools, services, and other solutions to increase their trustworthiness. Peer-to-peer Mentoring Programme: A programme to connect mentors and mentees on specific TTRAM topics, bridging gaps in the current landscape and building the peer-to-peer support attitude that the FIDELIS Network will thrive on. Open Training Activities: Different events which are open for all to join, designed to share and teach about different topics and solutions relevant to the repository community. They include webinars, which focus more on information sharing and topical discussions, and training interventions, which include some interactive element for the audience. A comprehensive training strategy has been developed based on the insights gathered from the landscape study, pilot testing, and the delivery of the first training activities. Through this, the different types of support were defined and refined, and will be delivered more widely in the first open calls next year. This deliverable report details the different choices made and topics considered around developing this strategy, as well as the outcomes of the pilot support round and further community engagement. This transparent presentation of rationale, considerations, and decisions made shows the community what can be expected from the FIDELIS Repository Training and Support Pillar and how repositories can participate in the different programmes and activities.
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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 | 0.062 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.115 | 0.027 |
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".