Research and analysis
GRADE UCAS data specification
Published 14 October 2021
Applies to England
© Crown copyright 2021
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Linking Dataset (Fact_db7)
The Linking Dataset contains applicants to the UCAS undergraduate scheme who still have an application that has not been canceled at the end of the cycle, and includes the following variables:
| Variable | Description |
|---|---|
| UIDP | Pseudonymised unique candidate identifier |
| Unique applicant identifier (one identifier per applicant per cycle) | Applicant identifier that is unique to each applicant in each cycle. |
Apply Qualifications Dataset (Fact_ac3)
The Apply Qualifications Fact Dataset is at qualification level and contain qualifications from applicants to the UCAS undergraduate scheme who are present in the Application Dataset. These qualifications are declared by the applicant during their application. This is limited to predicted A-level qualifications. The dataset includes the following variables:
| Variable | Description |
|---|---|
| Unique applicant identifier (one identifier per applicant per cycle) | Applicant identifier that is unique to each applicant in each cycle. |
| Application cycle | Cycle in which the applicant made their application. |
| Qualification status | Status of the qualification as declared by the applicant during application. For example ‘Pending’, ‘Gained’. |
| Qualification Description | Description of the type of qualification as declared by applicant during application. For example ‘GCE Advanced Level’. If no qualification description is provided during application, the value will be missing. |
| Subject Title | Subject of the qualification as declared by applicant during application. If no subject title is provided during application, the value will be missing. |
| Grade | Grade as declared by applicant during application. If no grade is provided during application, the value will be missing. |
| Year of qualification | Year the qualification was taken, as declared by the applicant. |
Applications Dataset (Fact_1da)
The Applications Dataset contains applications to the UCAS undergraduate scheme from applicants who have at least one application that has not been cancelled at the end of the cycle.
Applications from applicants who made their first application in a cycle after the June 30 deadline, but did not make a specific application to a course, are not included in this dataset.
All main scheme applications made before the June 30 application deadline which have not been cancelled by the of the application cycle are included in this dataset.
Only the most recent non main scheme application is included in this dataset. For example, if an applicant makes multiple applications through Clearing in an application cycle, only the most recent Clearing application is reported. Likewise, if an applicant makes multiple applications through Extra (ie. after each of their main scheme applications is rejected, but before the June 30 deadline), only their most recent Extra application is reported. Similarly, if an applicant makes an application through Extra, and then goes on to make an application through Clearing, only their most recent Clearing application will be reported.
Variables are reported in their state as at the end of each application cycle, unless otherwise specified.
When reporting Unconditional offer-making variables, June 30 deadline versions of variables should be used where possible (for example June30 subject line should be used instead of subject line).
Likewise, when reporting June30 HEP decision or June30 Applicant response, June 30 deadline versions of variables should be used where possible.
Some applications which were present in UCAS’ 2019 End of Cycle Unconditional offer making analysis (which were captured at the June 30 deadline) were subsequently cancelled, and so were not present at the end of the application cycle. These applications therefore are not present in this dataset.
Four applications have a value of 0 for the Main scheme application flag which contradicts their Application route value of ‘Main scheme’. This is a system error, and the main scheme application flag should be considered as the correct value. The application route is therefore not known.
In earlier cycles in this dataset, certain applicants were able to delay their response to applications. This functionality has not been reported on in this dataset as the feature is no longer present in the application system.
The dataset includes the following variables:
| Variable | Description |
|---|---|
| Unique applicant identifier (one identifier per applicant per cycle) | Applicant identifier that is unique to each applicant in each cycle. |
| Unique application identifier (one identifier per application per cycle) | Application identifier that is unique to each application made by an applicant. |
| Application cycle | Cycle in which the applicant made their application. |
| Entry year | Academic year in which course selected by applicant starts. Link with dimension table dim_7d7_entry_year. |
| Course identifier | A combination of provider and course code. |
| Detailed subject group (JACS3) | Two character code that classifies courses into a detailed level of 215 subjects. Each course is assigned up to three valid JACS3 subject codes (e.g. G100 - Mathematics) and a course balance indicator by UCAS, which are available for review by the provider. The course is assigned a subject based on these JACS3 subject codes and balance indicator, it largely correlates to the first two characters of the subject codes. Where there are more than one JACS3 subject codes for a given course, and the balance indicator is dual or triple, the first two characters of each subject code are reported in combination to a relevant category (e.g. Course with dual balance indicator with JACS3 subject codes L370 = Social Theory and M900 = Others in Law is assigned a subject ‘Y Combs of soc studies/law’). Please note: Between 2007 and 2011 the subject codes assigned to each course were from the JACS2.0 classification, therefore JACS3 versions of the subject categories have been approximated for 2007 to 2011 to allow a consistent time series. Also, since the 2019 application cycle, JACS3 versions of the subject categories have been approximated, after the discontinuation of the JACS subject grouping system. Link with dimension table dim_7d7_jacs3_sub_line. |
| HE provider code | Three character code unique to each Higher Education Provider. This is a mapped view of the Higher Education Provider as-at 2019. In the interest of keeping a consistent time series the HEP displayed is mapped from a previous HEP if a merger has occurred or the HEP has been renamed. E.g. In 2013 HEPs K05 and H50 merged, so all instances of H50 prior to 2013 will be reported as K05. Link with dimension table dim_7d7_HEP_code. |
| Application Route | One-digit code specifying route of application. Link with dimension table dim_7d7_application_route. |
| Provider decision (June 30 deadline) | Code specifying decision made by Higher Education Provider in response to an application. Decisions reported as they appeared on the application at the June 30 deadline. Link with dimension table dim_7d7_June30_HEP_decision. |
| Applicant response (June 30 deadline) | Code specifying applicant response to decision made by a Higher Education Provider. Responses reported as they appeared on the application at the June 30 deadline. Link with dimension table dim_7d7_June30_app_response. |
| HE provider code (June 30 deadline) | Three character code unique to each Higher Education Provider. Reported as it appeared on the application at the June 30 deadline. This is a mapped view of the Higher Education Provider as-at 2019. In the interest of keeping a consistent time series the HEP displayed is mapped from a previous HEP if a merger has occurred or the HEP has been renamed. E.g. In 2013 HEPs K05 and H50 merged, so all instances of H50 prior to 2013 will be reported as K05. Link with dimension table dim_7d7_HEP_code. |
| Course identifier (June 30 deadline) | A combination of provider and course code. Reported as it appeared on the application at the June 30 deadline. |
| Detailed subject group (JACS3) (June 30 deadline) | Two character code that classifies courses into a detailed level of 215 subjects. Each course is assigned up to three valid JACS3 subject codes (e.g. G100 - Mathematics) and a course balance indicator by UCAS, which are available for review by the provider. The course is assigned a subject based on these JACS3 subject codes and balance indicator, it largely correlates to the first two characters of the subject codes. Where there are more than one JACS3 subject codes for a given course, and the balance indicator is dual or triple, the first two characters of each subject code are reported in combination to a relevant category (e.g. Course with dual balance indicator with JACS3 subject codes L370 = Social Theory and M900 = Others in Law is assigned a subject ‘Y Combs of soc studies/law’). Please note: Between 2007 and 2011 the subject codes assigned to each course were from the JACS2.0 classification, therefore JACS3 versions of the subject categories have been approximated for 2007 to 2011 to allow a consistent time series. Also, since the 2019 application cycle, JACS3 versions of the subject categories have been approximated, after the discontinuation of the JACS subject grouping system. Reported as it appeared on the application at the June 30 deadline. Link with dimension table dim_7d7_jacs3_sub_line. |
| Main scheme application flag | Flag indicating whether the application was made before the June 30 application deadline. This is the final date by which an applicant can submit up to five applications to study on a course of higher education. Applicants who apply after this date go directly into Clearing. Please note that some applicants may apply and have their application withdrawn prior to the June 30 deadline, before having their application reinstated. These applications are considered as main scheme applications, but variables reported at the June 30 deadline will not be present (eg. June 30 Higher Education Provider code). |
| Accept flag | Flag to indicate whether applicant was placed through application. |
| Application flag | Flag set to 1 for each application. |
| UCAS unconditional offer making analysis flag | Flag indicating whether an application was used as part of UCAS’ 2019 end of cycle unconditional offer making analysis (only applications in the mainscheme made by English, Northern Irish and Welsh 18-year olds since the 2013 application cycle were considered). |
| Conditional unconditional offer flag | Flag indicating whether application received a conditional unconditional offer. Conditional unconditional offers are offers which are conditional at the point of offer, and adjusted by the provider from conditional to unconditional if selected as an applicant’s firm choice. These are identified in the admissions system through free text fields providers can use to communicate any additional information to applicants. Only calculated for applications considered in UCAS’ 2019 unconditional offer making analysis. |
| Direct unconditional offer flag | Flag indicating whether application received a direct unconditional offer. Direct unconditional offers are offers which are unconditional at the point of offer. Only calculated for applications considered in UCAS’ 2019 unconditional offer making analysis. |
| Other unconditional offer flag | Flag indicating whether application received an other unconditional offer. Other unconditional offers are offers which are conditional at the point of offer and become unconditional on or before June 30 - the final date on which main scheme applications can be submitted, and are not identified as a conditional unconditional offer. Only calculated for applications considered in UCAS’ 2019 unconditional offer making analysis. |
| Unconditional component flag | Flag indicating whether application received a an offer with an unconditional component. An offer with an unconditional component is any offer identified as an other unconditional offer, a conditional unconditional offer, or a direct unconditional offer. Only calculated for applications considered in UCAS’ 2019 unconditional offer making analysis. |
Entry Year Dimension Dataset (Dim_1DA_entry_year)
The Entry Year Dimension Dataset should be joined to the Fact_1DA dataset using the Entry_year variable, and includes the following variables:
| Variable | Description |
|---|---|
| Entry year | Academic year in which course selected by applicant starts. |
| Entry year | The academic year in which the course selected by the applicant starts. For courses starting between August and December the academic year is defined as starting in that year (i.e. for courses starting in August 2013 the entry year will be 2013.) For any courses starting earlier than September the academic year is defined as starting in the previous year. (I.e. for courses starting in January 2013 the entry year will be 2012 despite the course starting during the 2013 application cycle.) Please note: In each application cycle there are a small number of applications that are deferred for two years. |
Advertised Entry Requirements Dimension Dataset (Dim_1DA_entry_requirements)
The Entry Requirements Dimension Dataset contains A Level entry requirement data that is present for courses in Fact_1DA. Some courses have more than 1 observation per application cycle. The dataset should be joined to the Fact_1DA dataset using the Course_id and Application_cycle variables, and includes the following variables:
| Variable | Description |
|---|---|
| Course identifier | A combination of provider and course code. |
| Application cycle | Cycle in which the applicant made their application. |
| Name of qualification | Name of qualification on advertised course entry requirements |
| Required grades | Required grade profile on advertised course entry requirements |
| Additional requirement details | Additional details on advertised course entry requirements |
Detailed Subject Group (JACS3) Dimension Dataset (Dim_1DA_jacs3_sub_line)
The Detailed Subject Group (JACS3) Dimension Dataset should be joined to the Fact_1DA dataset using the jacs3_sub_line variable, and includes the following variables:
| Variable | Description |
|---|---|
| Detailed subject group (JACS3) | Two character code that classifies courses into a detailed level of 215 subjects. Each course is assigned up to three valid JACS3 subject codes (e.g. G100 - Mathematics) and a course balance indicator by UCAS, which are available for review by the provider. The course is assigned a subject based on these JACS3 subject codes and balance indicator, it largely correlates to the first two characters of the subject codes. Where there are more than one JACS3 subject codes for a given course, and the balance indicator is dual or triple, the first two characters of each subject code are reported in combination to a relevant category (e.g. Course with dual balance indicator with JACS3 subject codes L370 = Social Theory and M900 = Others in Law is assigned a subject ‘Y Combs of soc studies/law’). Please note: Between 2007 and 2011 the subject codes assigned to each course were from the JACS2.0 classification, therefore JACS3 versions of the subject categories have been approximated for 2007 to 2011 to allow a consistent time series. Also, since the 2019 application cycle, JACS3 versions of the subject categories have been approximated, after the discontinuation of the JACS subject grouping system. |
| Detailed subject group name | Name of detailed subject group. |
| Subject group name | Name of subject group. |
HE Provider Code Dimension Dataset (Dim_1DA_HEP_code)
The HE Provider Code Dimension Dataset should be joined to the Fact_1DA dataset using the HEP_code variable, and includes the following variables:
| Variable | Description |
|---|---|
| HE provider code | Three character code unique to each Higher Education Provider. This is a mapped view of the Higher Education Provider as-at 2019. In the interest of keeping a consistent time series the HEP displayed is mapped from a previous HEP if a merger has occurred or the HEP has been renamed. E.g. In 2013 HEPs K05 and H50 merged, so all instances of H50 prior to 2013 will be reported as K05. |
| HE Provider name | Name of HE provider. |
| HE provider tariff group | The grouping of HE providers based on the average levels of attainment of their accepted applicants (summarised through UCAS Tariff points) in a period of application cycles spanning from 2004 to 2011. Each group of providers accounted for around a third of all UK 18 year old acceptances in these cycles. Split by the following values: ‘Highe tariff’, ‘Medium tariff’, ‘Lower tariff’. |
| HE provider UK region | The UK region in which the provider is situated. Split by the following values: ‘North East’, ‘Yorkshire and The Humber’, ‘North West’, ‘East Midlands’, ‘West Midlands’, ‘East of England’, ‘London’, ‘South East’, ‘South West’, ‘Wales’, ‘Northern Ireland’, ‘Scotland’, ‘Overseas’. If the region of a provider has changed, the most recent region is reported. |
Application Route Dimension Dataset (Dim_1DA_application_route)
The Application Route Dimension Dataset should be joined to the Fact_1DA dataset using the Application_route variable, and includes the following variables:
| Variable | Description |
|---|---|
| Application Route | One-digit code specifying route of application. Link with dimension table dim_1DA_application_route. |
| Application route | The route through which an application was made. Main scheme: where the application was made before the June 30 deadline. Adjustment: where applicants who have met and exceeded the conditions of their firm choice choose to take up an alternative offer. Clearing: where an applicant either applied through main scheme clearing, after an applicant was unsuccessful in the main scheme, or direct to clearing, where the applicant has applied via Clearing without an initial application through the main scheme. Extra: where applicants who held no offers after using all of their main scheme choices, make additional choices. RPA: where an application is submitted to UCAS by an institution when an unconditional firm has already been offered and accepted by the applicant. |
Provider Decision (June 30 deadline) Dimension Dataset (Dim_1DA_June30_HEP_decision)
The Provider Decision (June 30 deadline) Dimension Dataset should be joined to the Fact_1DA dataset using the June30_HEP_decision variable, and includes the following variables:
| Variable | Description |
|---|---|
| Provider decision (June 30 deadline) | Code specifying decision made by Higher Education Provider in response to an application. Decisions reported as they appeared on the application at the June 30 deadline. |
| Provider decision (June30 deadline) | The provider decision at the June 30 deadline with the following values attached to applications: Conditional offer, Invited for interview, Decision pending, Unconditional offer, Unconditional course change, Rejected, Rejected by default, Course full, Application withdrawn, Provider yet to receive application (new application). Where no decision has been made for an application, the decision will be reported as missing. |
Applicant Response (June 30 deadline) Dimension Dataset (Dim_1DA_June30_app_response)
The Applicant Response (June 30 deadline) Dimension Dataset should be joined to the Fact_1DA dataset using the June30_app_response variable, and includes the following variables:
| Variable | Description |
|---|---|
| Applicant response (June 30 deadline) | Code specifying applicant response to decision made by a Higher Education Provider. Responses reported as they appeared on the application at the June 30 deadline. |
| Provider decision (June30 deadline) | The applicant response at the June 30 deadline with the following values attached to applications: Firm, Insurance, Declined by default, Declined, Cancelled. Where no reply has been made for an application, the applicant reply will be reported as missing. |
Applicant Dataset (Fact_33a)
The Applicant Dataset contains applicants to the UCAS undergraduate scheme who have an application that has not been cancelled at the end of the cycle. Some applicants who applied for the first time in an application cycle after the June 30 application deadline are present in the applicant fact dataset, but not in the application fact dataset, as they did not make a specific application to a course. The dataset includes the following variables:
| Variable | Description |
|---|---|
| Unique applicant identifier (one identifier per applicant per cycle) | Applicant identifier that is unique to each applicant in each cycle. |
| Application cycle | Cycle in which the applicant made their application. |
| Applicant domicile | Three-digit code specifying an applicant’s area of permanent residence. Link with dimension table dim_33A_applicant_domicile. |
| Applicant region (UK domiciled applicants only) | One-character code specifying an applicant’s UK region, linked by UCAS onto the home postcode declared by each applicant. Link with dimension table dim_33A_applicant_UK_region. |
| Gender | One-character code specifying gender as declared by the applicant. Link with dimension table dim_33A_applicant_gender. |
| Disability | One-character code specifying disability as declared by the applicant. Link with dimension table dim_33A_applicant_disability. |
| Ethnic Group | Two-digit code specifying ethnic origin as declared by the applicant. Link with dimension table dim_33A_applicant_ethnic_group. |
| Socio-economic group 2000 | One-digit code specifying socio-economic group 2000 as declared by the applicant. Link with dimension table dim_33A_applicant_socioecon2000. |
| Socio-economic group 2010 | One-digit code specifying socio-economic group 2010 as declared by the applicant. Link with dimension table dim_33A_applicant_socioecon2010. |
| POLAR3 Quintile | One-digit code specifying POLAR3 Quintile. Link with dimension table dim_33A_applicant_POLAR3. |
| POLAR4 Quintile | One-digit code specifying POLAR4 Quintile. Link with dimension table dim_33A_applicant_POLAR4. |
| Indices of multiple deprivation including: Index of Multiple Deprivation 2019 (English applicants only), Northern Irish Multiple Deprivation Measure 2017 (Northern Irish applicants only), Scottish Index of Multiple Deprivation 2012/2016 (Scottish applicants only), WIMD 2014 (Welsh applicants only). | One-digit code specifying Indices of multiple deprivation quintile. Link with dimension table dim_33A_applicant_IMD. |
| School Aligned Age | Derived from date of birth declared by the applicant, age is aligned with the cut off points for school/college cohorts within the different administrations of the UK. For England and Wales ages are defined on the 31 August, for Northern Ireland on the 1 July and for Scotland on the 28 February the following year. Defining ages in this way matches the assignment of children to school cohorts. For applicants outside of the UK the cohort cut off for England and Wales has been used. Please note: some applicants have listed their age as 0 or similar. Link with dimension table dim_33A_applicant_age. |
| Apply Centre Code | Code specifying the centre through which an applicant made their application. Link with dimension table dim_33A_apply_centre_code. |
| Application date | The date at which the applicant first applied in the application cycle. |
| Acceptance route | One-digit code specifying the route through which an applicant was accepted onto a course. Link with dimension table dim_33A_acceptance_route. |
| Applicant flag | Flag set to 1 for each applicant. |
| Accept flag | Flag indicating whether applicant was accepted on any of their applications in an application cycle. |
Domicile Dimension Dataset (Dim_33A_applicant_domicile)
The Domicile Dimension Dataset should be joined to the Fact_33A dataset using the Applicant_domicile variable, and includes the following variables:
| Variable | Description |
|---|---|
| Applicant domicile | Three-digit code specifying an applicant’s area of permanent residence. |
| Applicant domicile (named country) | Applicant’s area of permanent residence. This variable is derived from domicile as declared by the applicant on application. Split by individual country. Please note: The Channel Islands and the Isle of Man are considered outside the UK, and are therefore classified separately. |
| Higher level applicant domicile | Applicant’s area of permanent residence summarised to UK and global regions. This variable is derived from domicile as declared by the applicant on application. Split by the following values if domiciled in the UK: ‘England’, ‘Northern Ireland’, ‘Scotland’, ‘Wales’. Split by the following regions if Non UK: ‘EU (excluding UK)’, ‘Not EU’. Please note: The Channel Islands and the Isle of Man are assigned as ‘Not EU’. |
Region Dimension Dataset (Dim_33A_applicant_UK_region)
The Region Dimension Dataset should be joined to the Fact_33A dataset using the Applicant_UK_region variable, and includes the following variables:
| Variable | Description |
|---|---|
| Applicant region (UK domiciled applicants only) | One-character code specifying an applicant’s UK region, linked by UCAS onto the home postcode declared by each applicant. |
| Applicant region (UK domicile applicants only) | Applicant’s UK region. This variable is linked by home postcode as declared by the applicant on application. Split by the following values if domiciled in the UK: values if domiciled in the UK: ‘North East’, ‘Yorkshire and The Humber’, ‘North West’, ‘East Midlands’, ‘West Midlands’, ‘East of England’, ‘London’, ‘South East’, ‘South West’, ‘Wales’, ‘Northern Ireland’, ‘Scotland’, ‘Unknown’. Classified as ‘Overseas’ otherwise. |
| Applicant domicile | Applicant’s area of permanent residence summarised to UK and global regions. This variable is derived from domicile as declared by the applicant on application. Split by the following values if domiciled in the UK: ‘England’, ‘Northern Ireland’, ‘Scotland’, ‘Wales’. Classified as ‘Overseas’ otherwise. |
Gender Dimension Dataset (Dim_33A_applicant_gender)
The Gender Dimension Dataset should be joined to the Fact_33A dataset using the Applicant_gender variable, and includes the following variables:
| Variable | Description |
|---|---|
| Gender | One-character code specifying gender as declared by the applicant. |
| Gender | Gender as declared by the applicant. |
Disability Dimension Dataset (Dim_33A_applicant_disability)
The Disability Dimension Dataset should be joined to the Fact_33A dataset using the Applicant_disability variable, and includes the following variables:
| Variable | Description |
|---|---|
| Disability | One-character code specifying disability as declared by the applicant. |
| Disability | Disability as declared by the applicant by selecting from a list of available options. |
Ethnic Group Dimension Dataset (Dim_33A_applicant_ethnic_group)
The Ethnic Group Dimension Dataset should be joined to the Fact_33A dataset using the Applicant_ethnic_group variable, and includes the following variables:
| Variable | Description |
|---|---|
| Ethnic Group | Two-digit code specifying ethnic origin as declared by the applicant. |
| Ethnic Group (Summary Level) | High level grouping of ethnic origin as declared by the applicant: ‘White’, ‘Black’, ‘Asian’, ‘Mixed’, ‘Other’, ‘Unknown or Prefer Not To Say’. Please note: Ethnic origin is captured for UK domiciled applicants only, therefore all non UK domiciled applicants are assigned as ‘Unknown or Prefer Not To Say’. |
| Ethnic Group (Detailed Level) | Low level grouping of ethnic origin as declared by the applicant: ‘White’, ‘Black - Caribbean’, ‘Black - African’, ‘Black - Other Black background’, ‘Asian - Indian’, ‘Asian - Pakistani’, ‘Asian - Bangladeshi’, ‘Asian - Chinese’, ‘Asian - Other Asian background’, ‘Mixed - White and Black Caribbean’, ‘Mixed - White and Black African’, ‘Mixed - White and Asian’, ‘Mixed - Other mixed background’, ‘Other ethnic background’, ‘Unknown or Prefer Not To Say. Please note: Ethnic origin is captured for UK domiciled applicants only, therefore all non UK domiciled applicants are assigned as ‘Unknown or Prefer Not To Say’. |
Socio-economic Group 2000 Dimension Dataset (Dim_33A_applicant_socioecon2000)
The Socio-economic Group 2000 Dimension Dataset should be joined to the Fact_33A dataset using the Applicant_socioecon2000 variable, and includes the following variables:
| Variable | Description |
|---|---|
| Socio-economic group 2000 | One-digit code specifying socio-economic group 2000 as declared by the applicant. |
| Socio-economic group 2000 | The National Statistics Socio-economic Classification (NS-SEC) is an occupationally based system used to classify the adult population. Conditions such as pay and seniority of position are used to determine class. This is declared by the applicant, however please note a change in question in 2008. 2008 question: ‘If you are in full-time education, please state the occupation of the highest-earning family member of the household in which you live. If he or she is retired or unemployed, give their most recent occupation. If you are not in full-time education, please state just your own occupation’. Pre-2008 question: ‘If you are under 21, please state the occupation of the highest-earning family member of the household in which you live. If he or she is retired or unemployed, give their most recent occupation. If you are 21 or over, please state just your own occupation’. The response is captured for UK domiciled applicants only, therefore all non UK domiciled applicants are assigned as ‘Not classified / unknown’. |
Socio-economic Group 2010 Dimension Dataset (Dim_33A_applicant_socioecon2010)
The Socio-economic Group 2010 Dimension Dataset should be joined to the Fact_33A dataset using the Applicant_socioecon2010 variable, and includes the following variables:
| Variable | Description |
|---|---|
| Socio-economic group 2010 | One-digit code specifying socio-economic group 2010 as declared by the applicant. |
| Socio-economic group 2010 | The National Statistics Socio-economic Classification (NS-SEC) is an occupationally based system used to classify the adult population. The applicant is asked: ‘If you are in full-time education, please state the occupation of the highest-earning family member of the household in which you live. If he or she is retired or unemployed, give their most recent occupation. If you are not in full-time education, please state just your own occupation’. The applicant may then choose from 28,000 ONS job descriptions. These job descriptions are then mapped to 8 Socio-Economic Group codes via a lower level set of around 380 ‘2010 SOC Codes’. The response is captured for UK domiciled applicants only, therefore all non UK domiciled applicants are assigned as ‘Not classified / unknown’. Please note that, although the same 8 Socio-Economic Group codes are displayed in the Socio-economic group 2000 variable available from 2004-2014, occupations are mapped via a different set of ‘2000 SOC Codes’. Therefore, some job descriptions are mapped to different Socio-Economic Group values. |
| This is available from the 2015 application cycle onwards. |
POLAR3 Quintile Dimension Dataset (Dim_33A_applicant_POLAR3)
The POLAR3 Quintile Dimension Dataset should be joined to the Fact_33A dataset using the Applicant_POLAR3 variable, and includes the following variables:
| Variable | Description |
|---|---|
| POLAR3 Quintile | One-digit code specifying POLAR3 Quintile. |
| POLAR3 Quintile | Developed by HEFCE, POLAR3 classifies small areas across the UK into five groups according to their level of young participation in Higher Education. Each of these groups represents around 20 per cent of young people and is ranked from Quintile 1 (areas with the lowest young participation rates, considered as the most disadvantaged) to Quintile 5 (highest young participation rates, considered most advantaged). POLAR3 is based on the participation rates of young people between 2005 and 2009, who entered HE between 2005-06 and 2010-11 academic years. These groups are assigned using the postcode declared by the applicant. If a postcode is invalid, considered unsafe for measurement or there is no link to Census geography possible then the applicant is classified as ‘Unknown’. Please note: POLAR3 is only available for applicants domiciled in the UK, therefore any applicants domiciled outside of the UK are classified as ‘Unknown’. Also, although POLAR3 is available for applicants of all ages, it is recommended/most suitable for analysis of applicants aged 19 and under. |
POLAR4 Quintile Dimension Dataset (Dim_33A_applicant_POLAR4)
The POLAR4 Quintile Dimension Dataset should be joined to the Fact_33A dataset using the Applicant_POLAR4 variable, and includes the following variables:
| Variable | Description |
|---|---|
| POLAR4 Quintile | One-digit code specifying POLAR4 Quintile. |
| POLAR4 Quintile | Developed by HEFCE, POLAR4 classifies small areas across the UK into five groups according to their level of young participation in Higher Education. Each of these groups represents around 20 per cent of young people and is ranked from Quintile 1 (areas with the lowest young participation rates, considered as the most disadvantaged) to Quintile 5 (highest young participation rates, considered most advantaged). POLAR4 is based on the participation rates of young people between 2009 and 2014, who entered HE between 2009-10 and 2014-15 academic years. These groups are assigned using the postcode declared by the applicant. If a postcode is invalid, considered unsafe for measurement or there is no link to Census geography possible then the applicant is classified as ‘Unknown’. Please note: POLAR4 is only relevant for applicants domiciled in the UK, therefore any applicants outside of this cohort are classified as ‘Unknown’. Also, although POLAR4 is available for applicants of all ages, it is recommended/most suitable for analysis of applicants aged 19 and under. |
IMD Quintile Dimension Dataset (Dim_33A_applicant_IMD)
The IMD Quintile Dimension Dataset should be joined to the Fact_33A dataset using the Applicant_IMD variable, and includes the following variables:
| Variable | Description |
|---|---|
| Indices of multiple deprivation, including: Index of Multiple Deprivation 2019 (English applicants only), Northern Irish Multiple Deprivation Measure 2017 (Northern Irish applicants only), Scottish Index of Multiple Deprivation 2012 to 2016 (Scottish applicants only), WIMD 2014 (Welsh applicants only) | One-digit code specifying Indices of multiple deprivation quintile. Link with dimension table dim_33A_applicant_IMD. |
| Indices of Multiple Deprivation | The IMD variable differs depending on the applicant domicile: For England domiciled applicants, IMD relates to Index of Multiple Deprivation 2019. For Northern Irish domiciled applicants, IMD relates to the Northern Irish Multiple Deprivation Measure 2017. For Scottish domiciled applicants, IMD relates to Scottish Index of Multiple Deprivation 2012 to 2016. For Welsh domiciled applicants, IMD relates to Welsh Index of Multiple Deprivation 2014. Quintiles are assigned using the postcode declared by the applicant. If a postcode is invalid, considered unsafe for measurement or there is no link to Census geography possible then the applicant is classified as ‘Unknown’. Please note: IMD is only available for applicants domiciled in the UK, therefore any applicants domiciled outside of the UK are classified as ‘Unknown’. The Index of Multiple Deprivation for 2019 identifies small area concentrations of multiple deprivation across all of England, providing a relative measure of deprivation amongst small areas (Lower-layer Super Output Areas). When reporting by IMD 2019, it is used to group areas in each year in the time series. The Northern Ireland Multiple Deprivation Measure for 2017 identifies small area concentrations of multiple deprivation across all of Northern Ireland, providing a relative measure of deprivation amongst small areas (Super Output Areas). When reporting by NIMDM 2017, it is used to group areas in each year in the times series. The Scottish Index of Multiple Deprivation 2012 to 2016 identifies small area concentrations of multiple deprivation across all of Scotland, providing a relative measure of deprivation among small areas (data zones). In this report, a combination of the SIMD measures created in 2012 and 2016 has been used. SIMD 2012 is applied to all years before 2017, and SIMD 2016 is applied to years 2017 and onwards. The Welsh Index of Multiple Deprivation identifies small area concentrations of multiple deprivation across all of Wales, providing a relative measure of deprivation among small areas (Lower-layer Super Output Areas). This cycle, the WIMD 2014 has been used to group areas in each year in the times series. |
School Aligned Age Dimension Dataset (Dim_33A_applicant_age)
The School Aligned Age Dimension Dataset should be joined to the Fact_33A dataset using the Applicant_age variable, and includes the following variables:
| Variable | Description |
|---|---|
| School Aligned Age | Derived from date of birth declared by the applicant, age is aligned with the cut off points for school/college cohorts within the different administrations of the UK. For England and Wales ages are defined on the 31 August, for Northern Ireland on the 1 July and for Scotland on the 28 February the following year. Defining ages in this way matches the assignment of children to school cohorts. For applicants outside of the UK the cohort cut off for England and Wales has been used. Please note: some applicants have listed their age as 0 or similar. |
| Grouped school aligned age | School aligned age grouped into the following: ‘17 and under’, ‘18’, ‘19’, ‘20’, ‘20-24’, ‘25-29’, ‘30-34’, ‘35 and over’. |
Apply Centre Code Dimension Dataset (Dim_33A_Apply_centre_code)
The Apply Centre Code Dimension Dataset should be joined to the Fact_33A dataset using the Apply_centre_code variable, and includes the following variables:
| Variable | Description |
|---|---|
| Apply Centre Code | Code specifying the centre through which an applicant made their application. |
| Apply Centre Type | The type of the school or centre through which the application was submitted, giving an indication of the type of educational establishment attended by the applicant. The most recent school or centre type for each school code held by UCAS is displayed across the time series, regardless of the school or centre type at the time of the application. For example, academies were introduced 2012. When an Apply Centre Type is not found, it is classified as ‘Other’. |
| CentreNoP | A pseudonymised version of the National Centre Number of the school or centre through which the application was submitted. This is reported for schools for which UCAS holds a National Centre Number. The most recent National Centre Number for each school code held by UCAS is displayed across the time series, regardless of the National Centre Number at the time of application. When a National Centre Number is not found, it is classified as missing. |
Acceptance Route Dimension Dataset (Dim_33A_acceptance_route)
The Acceptance Route Dimension Dataset should be joined to the Fact_33A dataset using the Acceptance_route variable, and includes the following variables:
| Variable | Description |
|---|---|
| Acceptance route | One-digit code specifying the route through which an applicant was accepted onto a course. |
| Acceptance Route | The acceptance route with the following values attached to placed applications. Firm Choice: where the applicant has been accepted to their first choice. Insurance choice: where the applicant has been accepted to their second choice. Main Scheme Clearing: where an applicant was unsuccessful in the main scheme (i.e. applied before 30 June) and subsequently found a place using Clearing. Direct Clearing: where the applicant has applied via Clearing without an initial application through the main scheme. Adjustment: where applicants who have met and exceeded the conditions of their firm choice choose to take up an alternative offer - introduced in 2009. Extra: where applicants who held no offers after using all of their main scheme choices, make additional choices. RPA: where an application is submitted to UCAS by an institution when an unconditional firm has already been offered and accepted by the applicant. Please note: ‘Insurance choice’ and ‘Firm choice’ values are based on the applicant’s response to an offer as-at June deadline. There are 10,000 to 20,000 acceptances to a main scheme choice each year where the applicant has not responded, or is awaiting an offer, by June deadline. These acceptances are classified as ‘Other Main Scheme Choice’. |