REHOUSE public report: Report of Social requirements identified in the elicitation activities
Bibliographic record
Abstract
Summary: This REHOUSE report describes the social requirements elicitation process and related activities carried out in Task 1.2 “Social requisites elicitation” that aim to discover both stakeholders’ and end users’ needs to be considered in the design and development of the Renovation Packages (RPs). The deliverable suggests a methodology to identify what features are essential for these users, moreover, RP technology developers will verify if these requisites can be met in order to satisfy users’ needs providing effective solutions. In Section 2 a methodology based on a participatory approach is outlined presenting its adoption in the Italian demo-site to clarify objectives better and suggest methods to proceed. Section 3 is focused on a short description of the implementation of the survey in the four different demo-sites, in the respective countries: Italy, France, Hungary and Greece. A questionnaire was attached in the Annex to provide a protocol to allow the collection of comparable information, a working instrument for the survey.The aim is to gather the most useful information to well characterize users’ profiles, needs, barriers and critical features to thus better design and develop the solutions of their own RPs. Section 4 aims to explain the workflow for the optimisation of RPs, how the interview feedback can be used, how the items are functional to the work package requisites of each demo-site. The objective of the survey results analysis is to match end-users and stakeholders’ needs to the WPs requirements. For this purpose, a matrix is provided, to be used as a “dynamic” tool for the project life cycle. Further public reports of the REHOUSE project: Publications – REHOUSE
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 | 0.029 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.037 | 0.018 |
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".