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Apr 24 Modding Day


  • Submitted by: Luke Bosworth, l.p.bosworth@warwick.ac.uk
  • Submitted on: 11/10/2016
  • Revision; 4

Data File(s)

This data load contains 2 files, which are as follows:

File Content Size (bytes)
38985_Data.txt Main Data 4,315,242
38985_Notes_and_Labelling.xlsx Relevant description, including fields & columns 69,294

Source Dataset

HESA Destinations of Leavers Survey and Student Record 2014/15

Student data for this enquiry has been run using an updated HESA dataset (the fixed database) for the years 2014/15.

HESA Destination of Leavers survey 2014/15. Copyright Higher Education Statistics Agency Limited 2014 (HESA).

Destination of Full-time UK and EU domiciled leavers in paid employment only from Higher education institutions 2014/15 by Standard occupational classification (4 digit) Level of qualification obtained (Doctorate, Masters, Other Postgraduate, First degree, Other undergraduate) Qualification required for job Subject of study (2 digit JACS)

Population and restriction definitions
  • Coverage - Destinations of Leavers Survey
  • Activity - Used to identify if the student has entered employment
  • Mode of qualification - Refers to the method by which the qualification was achieved i.e. Full-time/Part-time.
  • Salary - The leaver's annual pay to the nearest thousand (£) before tax.

Student data for this enquiry has been run using an updated HESA dataset (the fixed database) for the years 2014/15. This dataset allows Higher Education Providers to re-submit specific elements of student data where a confirmed error had occurred in their initial return. Therefore, please be aware that where the fixed data has been used, it may not match HESA data published elsewhere.

Field Definitions

Data intelligence notes

Fields and Columns

  • ACYEAR - Academic year
  • F_SOCDLHE2010 - Standard occupational classification
  • F_LEVEL - Level of qualification obtained
    1. DOC - Doctorate
    2. MAS - Masters
    3. OPG - Other Postgraduate
    4. FID - First degree
    5. OUG - Other undergraduate
  • F_QUALREQ - Qualification required for job
    1. 11 - Yes: the qualification was a formal requirement
    2. 12 - Yes: while the qualification was not a formal requirement it did give me an advantage
    3. 13 - No: the qualification was not required
    4. 14 - Don't know
    5. Unk - Unknown
  • F_XJACS201NEW - Subject of study (2014/15)
  • F_XJACS201OLD - Subject of study (all values are 'na')
  • F_ZSIC2007 - Standard industrial classification
  • TOTAL - Number of cases (NB, this includes decimals since there is an apportionment of courses split between different areas).

HESA data

Any output must be rounded up/suppressed, in line with HESA instructions as set out in the Wiki and accompanying files.

One of the key objectives of LMI for All is to provide information on entry routes for specific occupations. HESA DLHE data offers potentially valuable insights into the higher education subjects previously studied by entrants into particular occupations, addressing the key question: “what subjects do people study prior to taking up a specific job?”

Users are interested in the profile of subject studied among members of the DLHE population who are in work, broken down by the occupation of their employment destination. The following illustrative example shows how the analysis might be presented by applications linked to LMI for All:

“Recent leavers from higher education working in this occupation studied the following subjects”. It is proposed to limit the top three subjects studied in terms of the proportion of people working in the occupation.

Therefore the core requirement from the DLHE dataset is for data relating to DLHE population (including Qualifiers population marker) in employment by subject category (JACS) and occupation (SOC 2010).

Users are also interested in the level of HE qualification studied / achieved. For example, it is potentially useful to know that x per cent of leavers from HE working in a given occupation had qualified at postgraduate level (compared with an overall average of y per cent).

The focus is on leavers who had pursued a full-time course entry routes into occupations and Part-time learners are often already established within an occupation.

Occupation is classified to 4-digit SOC 2010 Unit group. Some unit groups are poorly-populated in terms of HE leavers, such as routine manual occupations, because they are not typical graduate destinations. For SOC unit groups for which there are fewer than 50 responses in the DLHE the API should deliver analysis relating to the parent 3-digit category. In those instances in which the number of responses remains below 50 we would then move up to the 2-digit category.

Subject studied is classified to the 2-digit Principal subject of study.

The data / analysis made available via LMI for All is at the overall UK level only.

Descriptions of the data

Leavers from Higher Education Institutions classified by:

  • Standard Occupational Classification (SOC 2010) of employment at 4-digit level.
  • Level of qualification obtained (Doctorate, Masters, Other Postgraduate, First degree, Other undergraduate).
  • Qualification required for job.
  • Principal Subject of study (2 digit JACS).

The population of leavers is restricted using the following criteria:

  • Leavers in paid employment only
  • Leavers who had pursued a full-time course only
  • UK and European domiciled students working in UK at time of survey.

The DLHE survey is classified to SOC 2010.

F_XJACS201NEW and F_XJACS201OLD (data columns)

From the 38985_Field_Order_&Labelling_File.xlsx file

F_XJACS201NEWSubject of study (2014/15)VARCHAR2(3 CHAR)
F_XJACS201OLDSubject of study CHAR(2)

F_XJAC201OLD is now redundant and only contains 'na' - Not Applicable,


The file 38985_Notes_and_Labeling.xlsx contains three sheets.

Notes: describes the data provided by HESA to UKCES in general terms, including Field definition and links.

Field_Order: Shows the orders of the fields in the txt file

Field_Labelling: gives the detailed labels used for each of the fields used (e.g. occupations, levels and types of qualifications required and subject/disciplines)


Some occupations have a much stronger association with a specific course subject than others. For example, all doctors will have qualified in a relevant medical subject whereas corporate managers will have pursued a wider variety of subjects, with no single one dominating. The intention for LMI for All is simply to provide information on these patterns rather than presenting definite conclusions about formal entry requirements.

In those cases in which the profile of prior study is highly fragmented we could also apply a minimum threshold (e.g. a subject area is only presented if it accounts for a minimum of 10 per cent of respondents in the SOC category).

A key limitation of the DLHE data is that it only provides information about the initial destinations (six months after completion) of HE leavers rather than their employment activity in the medium to longer term.

Restricting Areas

To ensure that HESA is happy with the presentation of the data via the API initially areas to the data is restricted using an API key giving HESA the opportunity to review the dataset prior to its public release.

HESA will be given the opportunity to review the API guidance documentation relating to the HESA data in draft form prior to the publication of the data.

Permitted Purposes

Data may only be used to generate aggregate statistics for an on-line data portal ‘LMI for All’ which will allow third parties to obtain information on entry routes for specific occupations via an API.

Any data shared from the portal must be rounded to the nearest 5 according to the standard rounding methodology as outlined in special condition 1. Any data released via the API must relate to 50 or more leavers. The Data may not be made available in its entirety via the API.

Publication/Reproduction of the Data

Any reproduction or publishing of Data, subject to the above Permitted Purposes, must adhere to the HESA Services Standard Rounding Methodology.

All statistics published should be at a level of anonymisation and aggregation which will ensure that no Personal Data or Sensitive Personal Data are published, and thereby ensure the confidentiality of individuals.

HESA Services Standard Rounding Methodology:

  1. 0, 1, 2 must be rounded to 0
  2. All other numbers must be rounded to the nearest multiple of 5
  3. Percentages based on 52 or fewer individuals must be suppressed
  4. Averages based on 7 or fewer individuals must be suppressed
  5. Full-Time Equivalent data does not require rounding.


Example 1

Extract total for 2014/2015 in Production managers with First degree:
ACYEAR = 2014/15
F_SOCDLHE2010 = 1121

The number of cases with these characteristics is: 185.

Example 2

Extract total for 2014/2015 in Animal care services with Other undergraduate qualifications:
ACYEAR = 2014/15
F_SOCDLHE2010 = 6139

The number of cases with these characteristics is: 62.

Example 3

Extract total for 2014/2015 in Construction project managers with First degree that was a formal requirement:
ACYEAR = 2014/15
F_SOCDLHE2010 = 2436

The number of cases with these characteristics is: 168.

Example 4

Extract total for 2014/2015 in Sales and retail assistants with Other undergraduate qualifications and unknown qualification requirement:
ACYEAR = 2014/15
F_SOCDLHE2010 = 7111

The number of cases with these characteristics is: 144.

Example 5

Extract total for 2014/2015 in Medical practitioners in (A3) Clinical medicine:
ACYEAR = 2014/15
F_SOCDLHE2010 = 2211

The number of cases with these characteristics is: 5205.01.

data/hesa_dlhlv2.txt · Last modified: 2016-10-13 14:05 by David Owen