Crossing borders and boundaries:Positioning joint doctoral degrees as a capacity building initiative
Bibliographic record
Abstract
Doctoral education has evolved from the single isolated scholar on a lone knowledge quest into a diverse array of programme formats and supervisory arrangements. This diversity within doctoral education systems and structures include the crossing of national borders and institutional boundaries for both students and supervisors, sometimes through formal arrangements such as dual and joint degree programmes. While such arrangements have been in existence for some time, the research on the topic is limited, which often restricts our understanding to anecdotal evidence. Existing research also does not explore the complexities inherent to these arrangements when partnerships are forged between more than two partnering institutions, when North-South divides are crossed, when there are historical and current inequalities to navigate, and differences in structures, policies and practices across the partnering institutions. In parallel, there is the shared responsibility for the development of the doctorate candidates into early career researchers. This paper reports on an innovative funded transnational, structured joint doctoral degree programme in the field of higher education that involves three partnering institutions in the United Kingdom and South Africa, while also building skilled supervisory capacity. The programme sets out to support a cohort of doctoral staff-as-students within the three institutions exemplifying an internationalised curriculum underpinning the enhancement of supervisory capabilities at all three institutions, and the enrichment of their local research environments. The programme has the goal of transforming teaching, learning and research leading towards enhanced quality, success and equity in universities by establishing an academic pipeline (particularly in the South African context) that is transformative and disruptive yet equitable, and which addresses transformation imperatives in higher education. The programme demonstrates how foci on student development, staff development, and programme or curriculum development can be integrated. The key themes that delimit the project include equality, diversity, inclusion and well-being; transnationalisation, decolonisation and transformation of the curriculum; and developing creative spaces in higher education curricula. All the doctoral staff-as-student candidates projects fall within these delimited areas of interest. In the paper we explore what potential for innovation joint doctoral programmes of this nature may offer in terms of a) structuring collaborative spaces in doctoral programmes; b) development of early career researcher capacity (for both students and novice supervisors); and c) challenging institutional hierarchies and establishments.
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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 | 0.045 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.044 |
| Scholarly communication | 0.024 | 0.020 |
| Open science | 0.003 | 0.046 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".