代际流动 大学专业 药理学 计算机 法律
很多学生以为选专业只看兴趣和分数，英国的研究机构与监管机构却在算另一笔账：哪些本科专业真的能把出身普通的学生送进高收入群体。本文把 IFS 与 Sutton Trust 的流动率研究、gov.uk 上的官方参与率统计、OfS 官网的准入规则放在一起，讲清排名靠前的学科是谁、这些数字怎么算出来、以及在选科选校时能说明什么。
Choosing a degree is usually framed as a matter of interest and grades. In the UK, researchers and regulators ask a different question: which subjects actually move a student from a low-income household into the top end of the earnings distribution? This guide works through the IFS and Sutton Trust mobility research, the Department for Education participation statistics on gov.uk, and the OfS access rules, so you can see which subjects score highest on intergenerational mobility and how much weight the numbers deserve.
代际流动率怎么算：准入率乘成功率
代际流动率是一个乘法关系，准入率与成功率相乘得到一个百分比。准入率指某个大学、学科或具体课程里来自低收入家庭的学生比例，研究里用免费校餐资格作为代理指标。成功率指这些免费校餐学生在三十岁时进入收入分布前百分之二十的比例。一个专业如果只招到很少的普通家庭学生，准入率就低，哪怕毕业生收入很高，流动率也上不去。反过来，一个专业如果招了很多普通家庭学生，但毕业生大多停留在收入中段，流动率同样会被压低。很多学生以为流动率就是就业率或者起薪排名，这两者与它并不是一回事。把两个比率相乘的设计，逼着读者同时看入口和出口。
Mobility rate is defined as access rate multiplied by success rate, and both halves matter. The access rate is the share of students in a university, subject or course who come from low-income households, proxied by free school meal eligibility. The success rate is the share of those free school meal students who reach the top 20% of the earnings distribution by age 30. A course that admits very few lower-income students scores poorly on mobility even when its graduates earn a lot, and a course with wide access but ordinary graduate earnings is penalised just as heavily. Many students assume mobility rates are simply employment rates or starting-salary tables, which they are not.
全英平均一点三与基准线四点四
IFS 在 2021 年 11 月 24 日发布的报告给出的全英平均流动率是百分之一点三。基准线是百分之四点四，也就是收入群体准入完全平等、各家庭背景的学生进入前百分之二十的机会相同时应该出现的水平。两个数字差了三倍多，换算下来每一百名毕业生里只有一点三名同时满足出身低收入家庭与三十岁进入前百分之二十这两个条件。全英格兰只有七所院校达到或超过基准线，它们是伦敦玛丽女王大学、威斯敏斯特大学、伦敦城市大学、格林威治大学、伦敦南岸大学、布鲁内尔大学与圣乔治医院医学院。七所里有六所位于伦敦，城市与通勤圈的地理因素在准入端起了明显作用。很多学生以为高流动率一定来自高选择性院校，这份榜单给出的画面恰好相反。
The IFS report, published on 24 November 2021, puts the average mobility rate across English universities at 1.3%, against a benchmark of 4.4%. That benchmark is the rate you would see if access were equal across income groups and every background had the same chance of reaching the top 20% of earners. In practice, roughly one graduate in a hundred is both from a low-income household and inside that top fifth by age 30. Only seven institutions reach or beat the benchmark: Queen Mary University of London, Westminster, City, Greenwich, London South Bank, Brunel, and St George's, University of London. Six of the seven sit in London, which shows how strongly geography shapes the access side of the equation.
学科维度：药理学计算机与法律的流动率
学科层面最高的是药理学，流动率达到百分之四点二，明显高于基准线。计算机以百分之二点九位于次席，法律以百分之二点二紧随其后，这三个学科的准入率都不算窄，免费校餐学生在其中约占一成。药理学的高分来自两头都稳，招生面不窄，毕业生进入高收入区间的比例也高。艺术与人文学科整体表现偏弱，流动率普遍低于全英平均。这一段的读法要谨慎，学科口径是全英汇总，同一学科在不同院校之间的差距可能比学科之间的差距还大。把学科榜当成选专业的唯一依据，很容易忽略掉院校这一层的关键差别。
At subject level, pharmacology leads with a mobility rate of 4.2%, comfortably above the benchmark. Computing follows at 2.9% and law at 2.2%, and all three admit a comparatively broad intake, with free school meal students making up around one in ten of their cohorts. Pharmacology scores well on both halves at once, combining wide access with strong labour market outcomes. Arts and humanities subjects generally sit below the national average. Subject-level figures are national aggregates, so variation between universities inside one subject can be wider than the gap between subjects.
准入断层：私立学校学生进牛剑的机会
准入率的分化程度远超多数人的想象。在 2000 年代中期进入大学的群体里，私立中学背景的学生进入牛津或剑桥的可能性大约是免费校餐学生的 100 倍。这个倍数不是某个专业的个别现象，而是选择性院校招生结构的结果。低门槛院校的准入反而接近公平，普通家庭学生在其中的比例与他们在人口中的占比相差不大。两头分化说明，问题主要集中在最头部的那一小段院校。很多学生以为差距是逐年缓慢缩小的，官方统计给出的画面要复杂得多，后面几节会给出最新数字。
Access gaps vary enormously with institutional selectivity. Among people who entered university in the mid 2000s, students from private secondary schools were around 100 times more likely to attend Oxford or Cambridge than students eligible for free school meals. That ratio is not a quirk of one subject: it reflects how selective institutions recruit. At the least selective institutions, lower-income students are about as likely to attend as their wealthier peers, so the distortion sits at the very top of the sector rather than across it.
医学的准入反差：约二十五倍的差距
学科之间的准入差距同样明显。药理学与社会照护的准入差距很小，私营部门背景与免费校餐学生在这两个学科里的比例接近。医学是另一个极端，私立教育背景的学生就读医学的可能性约为免费校餐学生的 25 倍。医学的毕业生收入高，成功率并不低，但准入端过窄把流动率压了下来。很多学生以为收入高的专业自然就是改变出身最快的专业，医学正好是反例。判断一个专业对普通家庭是否友好，要把招生结构看的和毕业生收入一样重。
Subject-level access gaps look just as uneven. Pharmacology and social care show very small differences by socio-economic background, while medicine sits at the other end: privately educated students were nearly 25 times more likely to study medicine than those eligible for free school meals. Medicine produces high earnings and a solid success rate, yet its narrow intake drags the mobility rate down. Many students assume the highest-earning degrees are automatically the fastest route out of a low-income household; medicine is the cleanest counter-example.
准入与成功率的弱负相关
把各院校的准入率和成功率画在同一张图上，相关系数是负的零点二四。负号说明两者之间存在此消彼长的倾向，数值只有零点二四说明这种关系并不强。就业表现最好的院校招到的普通家庭学生偏少，准入率最高的院校其成功率又低于平均。两头都不占的院校数量不少，短板和长板往往同时存在。这个结构意味着单看一个指标会得出误导性的结论，判断一所学校要看它在两个维度上的位置。选校时把这两个数字摆在并排的位置，比记住一个总分有用。
Plotting universities by access rate and success rate gives a correlation of minus 0.24. The sign suggests a trade-off, while the size of the number says that trade-off is weak. Institutions with the strongest labour market outcomes admit relatively few lower-income students, and the institutions with the highest access rates tend to sit below average on success. Plenty of universities do reasonably well on both counts, which is why a single indicator misleads: what matters is a provider's position on both axes.
前二十门课程：伦敦院校的计算机法律与经济
把粒度降到具体课程，也就是某个学科在某所大学的那一种组合，前二十名的构成明显集中在伦敦。计算机、法律与经济在伦敦院校的组合反复出现在榜首，个别课程的流动率超过百分之十。另一端存在完全没有低收入家庭学生的课程，流动率因此是零。课程层面的差距是这份报告里最刺眼的一组数字，同一学科内部的选择差别可以决定一个学生是否进入高流动率的通道。学生最常把专业名称当成唯一的决策单位，实际影响更大的往往是院系所在的学校。
Narrowing the lens to courses, meaning a specific subject at a specific university, the top 20 is dominated by London providers. Combinations of computing, law and economics at London institutions appear again and again, and a handful of individual courses record mobility rates above 10%. At the other extreme, some courses enrol no students from low-income backgrounds at all and therefore score zero. Course-level variation is the sharpest finding in the report: within one subject, the choice of university can decide whether a student enters a high-mobility channel.
数据来源与时间口径：LEO 数据集
这些结论建立在 LEO 数据集上，它把学校记录、高等教育学籍与税务收入数据在个体层面连接起来。研究者主要观察 2000 年代中期入学的群体，他们的三十岁收入在数据截止时已经可以观测。时间口径决定了读法，这批人进入的是学费上限三千英镑时代的大学，今天的学费、贷款与就业市场都与当时不同。把结论当成长期结构判断是合理的，把它当成二零二零年代入学的精确预测则过度解读。数据只覆盖英格兰，苏格兰、威尔士与北爱尔兰的院校不在其中。常见的错误是引用数字却不写年份与数据来源，读者于是分不清这是哪一届学生的故事。
The findings rest on the Longitudinal Education Outcomes dataset, which links school records, higher education enrolment and tax records at the individual level. The analysis centres on people who started university in the mid 2000s, because their earnings at age 30 can already be observed. That timing shapes how the results should be read: this cohort studied under the three-thousand-pound fee cap, in a labour market very different from today's. Treat the numbers as a structural finding rather than a precise forecast for students starting in the 2020s, and note that the data cover England only.
官方最新口径：教育部参与率统计
判断准入端的最新状况，要看教育部在 gov.uk 上发布的官方统计。2026 年 7 月 9 日发布的一期显示，按十九岁前进入高等教育的比例计算，整体参与率是百分之四十四点七，低于上一届的四十六，但仍高于疫情前的四十四点五。免费校餐学生的参与率是百分之二十八点六，连续三年下滑，略高于疫情前的百分之二十八点二。两类学生的参与率差距是十九点八个百分点，为最近四年最小，却比疫情前的十八点七个百分点更大。进入高门槛院校的差距是九点三个百分点。这些数字呈现的是走走停停的改善，而不是持续收敛。这一期的口径也有变化，它第一次把原来的参与度统计并入同一份发布。
To judge where access stands now, use the Department for Education statistics published on gov.uk. The release dated 9 July 2026 puts the overall participation rate by age 19 at 44.7%, down from 46.0% for the previous cohort but still above the pre-pandemic 44.5%. Participation among free school meal students was 28.6%, falling for a third consecutive year yet marginally above the pre-pandemic 28.2%. The gap between the two groups was 19.8 percentage points, the narrowest in four years but wider than the 18.7 points recorded before the pandemic, and the high tariff gap stood at 9.3 points. The trend is stop-start improvement rather than steady convergence, and the release also merges the former participation measures series into one publication.
政策端：OfS 的准入与参与计划
政策工具落在 OfS 官网公布的准入与参与计划上。英格兰的高校如果在核准学费上限类别注册，并希望收取高于基本学费上限的费用，就必须持有一份获批准的计划，依据是 2017 年高等教育与研究法以及注册条件 A1。现行方法要求高校把重点放在机会平等风险上，并参照 OfS 发布的机会平等风险登记册，计划正文不得超过三十页。这些规则把流动率讨论从研究话题变成了院校每年必须提交的合规文件。很多学生以为这类文件与自己无关，实际上它决定了学校在招生宣传与资助上的动作方向。查一所学校愿意在哪些学生群体上投入，比看它的宣传语更能说明问题。
The policy lever is the access and participation plan, published through the OfS website. An English provider registered in the approved fee cap category must hold an approved plan if it wants to charge above the basic tuition fee cap, under the Higher Education and Research Act 2017 and registration condition A1. The current approach asks providers to frame their plans around risks to equality of opportunity, using the OfS Equality of Opportunity Risk Register, and caps a plan at 30 pages. This turns a research finding into an annual compliance document, which is why the numbers behind it matter to applicants and not only to administrators.
常见误读：把流动率当成专业排名
常见的错误之一是把流动率当成专业排行榜，它衡量的是多少低收入家庭学生最终进入高收入区间，与课程质量或教学水平不是同一个概念。招生规模小而窄的学科容易出现极端值，药理学的高分与它的招生结构和职业路径直接相关，不能简单搬到别的学科。第二个常见错误是忽略样本时间，2000 年代中期入学的群体面对的是另一个就业市场与另一套学费。第三个常见错误是把成功率的定义记错，前百分之二十指三十岁时的收入分布位置，不是毕业起薪。把定义读准，比记住名次有用得多。
Three misreadings recur. The first treats mobility rates as a ranking of course quality, when the measure asks how many lower-income students end up in the top earnings bracket, which is not the same thing as good teaching. Small, narrow subjects are prone to extreme values, and pharmacology's headline figure reflects its intake structure and career route rather than a general rule. The second ignores the cohort: people who started in the mid 2000s faced a different labour market and a different fee regime. The third mixes up the success rate, which is a position in the earnings distribution at age 30 and not a starting salary.
选科选校时怎么用这些数据
用这些数据做决定，先看方向再看名次。学科方向上，药理学、计算机与法律在流动率上表现最好，经济与法律在伦敦院校的课程组合里同样靠前。院校方向上，去 OfS 官网查该校的准入与参与计划，看它列出的风险与干预措施是否落在你所属的学生群体上。再把教育部的参与率统计与自己的目标院校对照，判断这所学校在准入端的位置。很多学生把选校完全交给排行榜，实际上同一学科在不同院校的差距可以比学科之间的差距更大。这些指标衡量的是群体概率，它不能替一个具体的人做决定，但能帮你看清哪些路径的门是开着的。
Used well, these figures point to directions rather than positions. On the subject axis, pharmacology, computing and law record the highest mobility rates, and combinations of economics and law at London providers also rank near the top. On the institutional axis, check a provider's access and participation plan on the OfS website and see whether the risks it names apply to students like you, then compare its position in the DfE participation statistics with your shortlist. Many students outsource the decision to league tables, even though variation inside one subject can exceed the gap between subjects. One caveat remains: these are group probabilities, not a prediction about any individual.
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