Data Insights

Key Research Findings

Our mixed-methods analysis has uncovered significant structural discrepancies and confidence gaps that hinder equitable access to AI doctoral studies.

1. Global Ambition vs. National Restriction

Our NLP analysis of 2,643 PhD listings revealed a critical misalignment we term the "False Hope" barrier.

While the vast majority of UKRI-funded projects advertise themselves as open to "Worldwide" applicants, the underlying funding structures typically cap international recruitment at 30%. Coupled with high visa costs, this creates a system that invites global talent but structurally excludes it.

79.2%
Advertised Openness
30%
Real Intake Cap

Fig 1. The discrepancy between advertised eligibility and funding reality.

2. The Confidence Gap

"Even among students with identical academic backgrounds in STEM, those from lower socio-economic backgrounds reported significantly lower 'AI Self-Efficacy' scores on the AILIT-S scale."

Qualitative Interview Insight

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