Manual approach

Measuring gender balance doesn’t have to be complex. Albeit more time-consuming and better suited for small-scale analyses, keeping track of sources using an excel spreadsheet is a simple and readily available alternative to automated or bespoke tools.

BBC 50:50

Teams participating in the BBC’s 50:50 project keep track of the number of men and women contributors featured in their output and share the data with each other on a monthly basis. Due to the diversity of the programmes involved, the metrics and measuring system can be adapted to keep things fair.


You can also use WIN’s metrics and suggestions outlined in this guide. You can pick and choose from the list of metrics or adapt them based on your own needs. We’ve also developed a simple, but handy excel tool to help you record your data and show progress over time.

There are a number of different metrics that can be used to measure gender balance. The below are options which you can pick and choose from and adapt. It is important to track text as well as images:


A simple way to track how prominent women are is to compare the number of women mentioned in an article vs. the number of men mentioned. A ‘mention’ includes any reference to a man or a woman. This could be a name, a pronoun (she, he, her, his, him, etc.), a title (Mr, Mrs, Miss, Ms, Sir, Lady, Dame, etc.), a gendered noun (girlfriend, boyfriend, daughter, son, wife, husband, etc.). You could adapt this metric to count names only, or specific pronouns such as she vs. he.

  • Metric % mentions of women vs. men
  • Formula # mentions of women DIVIDED BY total # mentions of women plus men
  • Target 50%


Comparing the number of women who appear as main characters in a story vs. the number of men is another simple measure of the prominence of women in your coverage. A ‘main character’ can be the subject or one of the subjects of the story. Or it can be someone who is quoted, sourced or mentioned repeatedly throughout. A story can have more than one main character.

  • Metric % main characters that are women
  • Formula # women main characters DIVIDED BY total # main characters (i.e. women PLUS men)
  • Target 50%


You can assess the prominence of women in images by looking at the proportion of ‘people images’ with women as the only or main subject. A ‘main subject’ can be the only subject or one of prominent subjects in an image. This does not include women in the background. An image can have more than one subject.

  • Metric % people images where women are a main subject
  • Formula # images with women as main or only subjects DIVIDED BY # images of people
  • Target 50%


Tracking the proportion of women sources gives a clear idea of the level of inclusion of women’s voices and opinions. A ‘source’ can be someone giving an account of a personal experience or opinion, a witness, a spokesperson or an expert. A ‘source’ includes someone who is quoted directly or indirectly and is measured by counting the number of direct and indirect quotes. It is also possible to count direct quotes only, for ease. A source should only be counted once, regardless of how many times they are quoted. To get an accurate measure, sources where the gender is unknown or a plural is used should be excluded.

  • Metric % unique women quotes
  • Formula # unique women sources DIVIDED BY total # unique sources
  • Target 50%


Focusing on expert sources rather than sources overall high-lights the inequality in the types of source being used. An ‘expert source’ is someone with expert knowledge or power to influence, quoted directly or indirectly. This could be a judge, an academic, a CEO or business person with sector knowledge, a politician, a police chief etc. The approach to measurement is the same for ‘sources’ above, with an expert source only being counted once, regardless of how many times they are quoted.

  • Metric % unique women expert quotes vs. unique men expert quotes
  • Formula # unique women expert sources DIVIDED BY total # expert sources
  • Target 50%


Author voice is an important indicator too. The proportion of women bylines is a simple and powerful metric. It is best if this is analysed by the category of news content as well as the over-all publication, as there tends to be a women byline ‘deficit’ in ‘heavy’ content categories such as politics, business and sport. Bylines where the author is not known should be excluded from the overall count.

  • Metric % women bylines
  • Formula # women bylines DIVIDED BY total # bylines (DISAGGREGATED by category)
  • Target 50%


Assessing whether content contains gender stereotyping and sexist language requires a nuanced understanding of what this means (see section X).This is a difficult category to measure because it can require subjective decisions. A basic method is to count any article with one or more instances of gender stereotyping or sexism. There is a difference between gender stereotyping language that is mild and unintentional vs. overt and offensive sexist language and so you may want to track these separately or to score articles based on the number of instances of language found.

  • Metric % articles containing sexist or gender stereotyping language
  • Formula # articles with 1 or more instances of gender stereotyping or sexist language DIVIDED BY total # articles
  • Target 0%


Images can also be used to measure the degree of gender  stereotyping. This involves calculating the proportion of images of women that are sexist or gender stereotyping. It is possible to adjust this metric to differentiate between mild, medium or strong gender stereotyping/sexist images.

  • Metric % sexist or gender stereotyping images of women
  • Formula # images of women that are gender stereotyping or sexist DIVIDED BY total # images of women with women as main or only subjects
  • Target 0%
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