Moderator’s Guidelines and Policy

Scope

The Moderator’s Guidelines and Policy outlined below covers the moderation of user-submitted posts to the Unequal Stories website.

Moderation aims

The moderation of user-submitted posts has five main functions:

  1. To ensure the anonymity of users is protected given that the posts might contain potentially sensitive information.
  2. To tag the user posts under emerging themes which will then be visualised on the Unequal Stories map.
  3. To protect the safety or integrity of our platform, including preventing spam, abuse, or malicious actors on our services.
  4. To mark any topics that are potentially upsetting but are deemed pertinent to the research with a sensitive content disclaimer.
  5. To edit the posts for clarity which might include correcting grammar and spelling.

Given the nature of the study, it is expected that some content might be sensitive and/or contentious.

If you feel you have been defamed or libelled in a post, or that a post is putting yourself or someone else at risk your first step should be to contact the Moderator to have the post removed at unequalstories@falmouth.ac.uk

It is up to the moderator’s discretion to remove the post based on your complaint.

Disclosure control policy

Although the user posts are anonymous, there is a potential risk that by disclosing personal and potentially sensitive stories on a publicly accessible website individuals might be identifiable and thus risk retaliation. This risk will be mitigated by a moderation process and a disclosure control policy which will:

  1. Remove any reference to specific faculties, departments, employers or individuals before publishing the stories online.
  2. Replace precise geographic locations with broader provincial or county references (for example, ‘Springs’ will be replaced with ‘Gauteng’ or ‘Redruth’ will be replaced with ‘Cornwall’).
  3. Apply a rounding methodology to any personal data. This will be based on a Standard Rounding Methodology as specified by HESA and will use the following rules:
    • All numbers will be rounded to the nearest multiple of 5.
    • Any number lower than 2.5 will be rounded to 0.
    • Halves will always be rounded upwards (e.g. 2.5 is rounded to 5).
    • Percentages based on fewer than 22.5 individuals will be suppressed.
    • Averages based on 7 or fewer individuals will be suppressed.
    • The above requirements apply to headcounts, FPE and FTE data.
    • Financial data will not be rounded.

Key areas for consideration when applying the rounding methodology will include any personal data revealing racial or ethnic origin, political opinions, sexual orientation, religious or philosophical beliefs or trade-union membership.

Ownership and Liability of Posts

Messages posted at this site are the sole opinion and responsibility of the poster.