‘Science’- of value to hazard & disaster challenges; an exposé on interdisciplinary research
Bibliographic record
Abstract
In the Indian Himalaya, ongoing, multi-disciplinary, tri-lateral (Canada, India, UK), participatory (light) research is exploring interconnected questions of mountain system process-hazard dynamics, community heritage-vulnerability- resilience conditions, and rapid development implications (e.g. HEP) in the context of international sustainable development and disaster risk reduction policy accords, in order to fashion a more sustainable future. Pursuing this hybridisation of themes has required large shifts across traditional intra/inter subject boundaries, and so many lessons have already been learned. This approach has without doubt been hugely beneficial in delivering an enhanced level of knowledge involving a range of non-academic organisations and communities speaking their local languages. Here we draw upon these research experiences, making the case that physical sciences are very much part of the effort to seek better understanding of and futures for the world, where a holistic understanding has to draw upon the in-depth approaches and outcomes of a range of disciplines. We seek to show the benefits of this approach to date, but equally to generate debate around a number of contentions; a challenge we should embrace together: (1) Current thinking suggests that Interdisciplinarity has great potential to provide something greater than the sum of its parts. We suggest that this needs to be a genuine meeting of minds and a willingness to work together on the part of all the players. Hence we ask ‘interdisciplinarity for whom and using who’s methods?’ (2) Is this interdisciplinary endeavour merely following an in-vogue paradigm and being used as a vehicle of power for some parts of the interdisciplinary whole? Indeed disciplinarity seems to be negatively cast, being touted as a dirty word by some. But let’s not forget if we don’t develop discipline based knowledge, with parity, then we fail to populate cross-disciplinary endeavours with an improving knowledge and technique baseline, this will in due course stifle the progress of interdisciplinarity. Hence lets not throw out the baby with the bathwater! (3) Employers delivering technical services do still seek depth of disciplinary knowledge, so we need to create degree programmes that deliver societally relevant depth and breadth- this calls for a mix of the old and the new, not just radicalism! (4) The language and approach of interdisciplinarity to date generates genuine discomfort in the scientific community- this we cannot ignore; together, we need to co-produce a better model of interdisciplinarity that fully embraces all of the disciplines represented in any project partnership. These are not mindlessly provocative, anachronistic denials of the world; but instead genuinely open reflections of earth scientists/ geographers who do work in an already diverse discipline and more so across boundaries. We all have to talk, in common tongue, seeking to understand the array of contributions that can be brought into the mix, otherwise interdisciplinarity will develop within intrinsic bias/ reduced capacity and therefore fall short in optimising pathways to impact. This was a Dec 2016 presentation, which we re-discuss with a different multi-disciplinary audience
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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; both teacher heads agree on what is shown here.
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".