Fixed 403 links in guides where possible.

content/content-guide/our-style/inclusive-language.md

@@ -92,7 +92,7 @@ When referring to a person’s race or ethnicity, use adjectives, not nouns (for
 
 ### Media style guides for race, ethnicity, and religion
 
-- [National Association of Black Journalists Style Guide](http://www.nabj.org/?styleguide)
+- [National Association of Black Journalists Style Guide](https://nabjonline.org/news-media-center/styleguide/)
 - [Guidance from the Asian American Journalists Association](https://www.aaja.org/news-and-resources/guidances/)
 - [Native American Journalists Association Reporter's Indigenous Terminology Guide](https://najanewsroom.com/wp-content/uploads/2018/11/NAJA_Reporting_and_Indigenous_Terminology_Guide.pdf)
 - [Religion Newswriters Association's Religion Stylebook](http://religionstylebook.com/)

content/engineering/our-approach/people/assessment.md

@@ -91,7 +91,7 @@ Now you’ve got a bunch of feedback, so the next step is to synthesize it down
 
 First, you’ll want to review all that feedback along with the person’s facilitator (if applicable). You’re looking for patterns, commonalities, or feedback that aligns with what you or the facilitator have personally observed. You’re looking to distill down all that feedback into a review for each critical element in the person’s performance profile. Include as many specific examples of behavior as possible — good feedback is specific and actionable (for a deeper treatment if this idea, see this article on [The Situation-Impact-Feedback Tool](https://www.mindtools.com/pages/article/situation-behavior-impact-feedback.htm)).
 
-It’s important to be especially cognizant of unconscious bias here. Remember that people are especially susceptible to assume that underrepresented people in tech — women, people of color, etc. — are less qualified than their white male counterparts. One way to correct for this bias is to make sure that reviews are concrete and specific (as above). Another way is to be cognizant of the kinds of reviews that are especially applied to underrepresented minorities. For example, [the word “abrasive” is far more common in reviews of women than of men](https://www.fastcompany.com/3034895/strong-female-lead/the-one-word-men-never-see-in-their-performance-reviews). Other similar kinds of phrases to watch out for are “tone”, “aggressive”, “judgemental”, “too nice”, and so on. In general do not write a review that seems like it speaks to the person’s character. Reviews should be focused on outcomes and project work. 
+It’s important to be especially cognizant of unconscious bias here. Remember that people are especially susceptible to assume that underrepresented people in tech — women, people of color, etc. — are less qualified than their white male counterparts. One way to correct for this bias is to make sure that reviews are concrete and specific (as above). Another way is to be cognizant of the kinds of reviews that are especially applied to underrepresented minorities. For example, [the word “abrasive” is far more common in reviews of women than of men](https://www.fastcompany.com/3034895/the-one-word-men-never-see-in-their-performance-reviews). Other similar kinds of phrases to watch out for are “tone”, “aggressive”, “judgemental”, “too nice”, and so on. In general do not write a review that seems like it speaks to the person’s character. Reviews should be focused on outcomes and project work. 
 
 GSA has [guidance on writing objective and fair reviews](https://insite.gsa.gov/cdnstatic/insite/Appraising_Objectively_and_Fairly.pdf) that’s worth reviewing as you start to write your review.