House of Commons Library: Briefing Paper Number 8538, 16 March 2020: The Review of University Admissions
Bibliographic record
Abstract
In the UK prospective students apply for university places through the UCAS administrative system.Students applying through UCAS are required to submit various types of information including: predicted exam grades, a personal statement and academic references.Universities assess the information provided by candidates and offer students places based on a holistic assessment of all the data provided.The university admissions system has been under scrutiny for decades and reviews have been conducted such as the Schwartz Review in 2004.Tweaks have been made to the system as a result of these reviews, but a number of criticisms remain.Current concerns are focused on the use of predicted grades and unconditional offers and in particular on their impact on disadvantaged students.The minority of university offers are unconditional, but the share of all offers made that were recorded as unconditional has increased significantly, from 9.2 per cent in 2013, to 15.1 per cent in 2018.Most unconditional offers are made to older students, but the unconditional offer rate for 18 year olds has driven the overall increase in unconditional offers.In 2013 1.1% of 18 year old applicants received at least one unconditional offer, by 2019 this had increased to 37.7%.Unconditional offers are more common at universities with lower entry requirements.In 2013 just 16 universities had unconditional offer rates to 18 year olds of 1% or more.In 2019 this number had increased to 88.This rise in unconditional offers has been attributed to the increasingly competitive market in higher education and the raising of tuition fees in 2012.The rapid rise in the number of unconditional offers made is seen as concerning as unconditional offers may be de-motivating for students and lead to under achievement in exams.Various reforms have been suggested to the admissions system such as moving to some type of post qualification application (PQA) scheme and the increased use of contextualised admissions.On 14 August 2019 the Labour Party announced its support for a PQA system.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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; 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".