Bibliographic record
Abstract
Housing research is very diverse operating across many disciplines. It is characterised by a broad range of methods, approaches and purposes. It is also very fragmented with researchers having very little sense of how different types of research relate to one another. If we are to promote collaboration among researchers and find solutions to our pressing housing problems, we need a framework which will hold this diversity together. Housing research is about asking and answering questions. Few researchers, however, reflect upon the questions they ask and the type of answer their questions anticipate. This paper proposes ‘a framework for collaborative creativity’. It contends that if we examine the questions underpinning all these different research methods, we will find that each is primarily oriented towards answering a particular question within a group of eight questions. The paper proposes that a scientific approach to housing consists of asking a complete set of eight inter-related questions: an empirical question, a theoretical question, an historical question, an evaluative/critical question, a transformative question, a visionary/policy question, a strategic question and a practical question. These questions are functionally inter-related, they provide a framework for inter-disciplinary collaboration and, they are ongoing and cyclic producing cumulative and progressive results. Housing researchers can distinguish these eight questions by reflecting upon themselves and their work. The paper draws upon a discovery by Bernard Lonergan, a Canadian methodologist, philosopher, theologian and economist ([1957]1992, [1972]1990).
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 | 0.027 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.009 | 0.064 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".