Gender is gender: male or female! <\/p>\n\n\n\n
Of course it’s not! First of all that be clear that we (J&I, OMbook!) do think the old distinction between gender as psychosocial identity and sex as the physiological\/genetic substrate is moderately important. However, even there, though Donald Trump and others may deny it, things aren’t simply binary because genetic sex though it’s mostly XX or XY isn’t quite that simple with XO, XXY and other even rarer genotypes. <\/p>\n\n\n\n
Then “phenotypic”, i.e. physiological, anatomical gender differences, aren’t just about the X and Y chromosomes, much else, some genetic, affects how the sex chromosomes impact on the phenotype.<\/p>\n\n\n\n
Sociopolitically, gender now is of course highly contentious with a powerful and important reaction against “binary” and so often misogynist and heterosexist ways of seeing it. We love the increasing respect for intersex and transgendered individuals in many countries (but not all of course). <\/p>\n\n\n\n
This raises some interesting challenges if coding gender. The UK has lagged behind many countries in officially moving from a binary categorisation of gender but different countries that have created non-binary categories have different systems. This situation means that gender remains an absolutely crucial variable in therapy research and routine data collection but is now vexed. More on that in another post: Gender categories (in quantitative research)<\/a>.<\/p>\n\n\n\n Even when a some non-binary category system is offered the vast majority of clients outside specialist gender identity clinics still own, with or without some reservations, one of the old M\/F binary. This means that even if we have one or more non-binary codes for gender analyses of data for the one or more non-binary categories is challenged by a very small cell size”others” for data from individual therapists and even from small services (“internal” data analyses). At the same time, the lack of a non-binary category system (in the UK at least) means that there is little or no referential data in large aggregate datasets to support “external” analyses for those choosing a non-binary gender identity and such “external” analyses comparing across various datasets can hit problems where different non-binary categories were on offer.<\/p>\n\n\n\n I have gone into more detail in a separate post: Gender categories (in quantitative research)<\/a><\/p>\n\n\n\n Cell size<\/a> We assume that gender is important throughout the book but tried not to jump to binaries or to oversimplify things!<\/p>\n\n\n\n Created 14.xi.21, tweaks and updated links 20.x.26.<\/p>\n","protected":false},"excerpt":{"rendered":" Gender is gender: male or female! Details Of course it’s not! First of all that be clear that we (J&I, OMbook!) do think the old distinction between gender as psychosocial identity and sex as the physiological\/genetic substrate is moderately important. However, even there, though Donald Trump and others may deny it, things aren’t simply binary … Continue reading Gender<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","template":"","meta":{"footnotes":""},"doc_category":[18],"doc_tag":[],"glossaries":[],"knowledge_base":[],"class_list":["post-2650","docs","type-docs","status-publish","hentry","doc_category-om-book"],"year_month":"2026-10","word_count":416,"total_views":"1482","reactions":{"happy":"0","normal":"0","sad":"0"},"author_info":{"name":"chris","author_nicename":"chris","author_url":"https:\/\/www.psyctc.org\/psyctc\/author\/chris\/"},"doc_category_info":[{"term_name":"All OM book glossary entries","term_url":"https:\/\/www.psyctc.org\/psyctc\/glossary\/non-knowledgebase\/om-book\/"}],"doc_tag_info":[],"knowledge_base_info":[],"knowledge_base_slug":[],"_links":{"self":[{"href":"https:\/\/www.psyctc.org\/psyctc\/wp-json\/wp\/v2\/docs\/2650","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.psyctc.org\/psyctc\/wp-json\/wp\/v2\/docs"}],"about":[{"href":"https:\/\/www.psyctc.org\/psyctc\/wp-json\/wp\/v2\/types\/docs"}],"author":[{"embeddable":true,"href":"https:\/\/www.psyctc.org\/psyctc\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.psyctc.org\/psyctc\/wp-json\/wp\/v2\/comments?post=2650"}],"version-history":[{"count":6,"href":"https:\/\/www.psyctc.org\/psyctc\/wp-json\/wp\/v2\/docs\/2650\/revisions"}],"predecessor-version":[{"id":5542,"href":"https:\/\/www.psyctc.org\/psyctc\/wp-json\/wp\/v2\/docs\/2650\/revisions\/5542"}],"wp:attachment":[{"href":"https:\/\/www.psyctc.org\/psyctc\/wp-json\/wp\/v2\/media?parent=2650"}],"wp:term":[{"taxonomy":"doc_category","embeddable":true,"href":"https:\/\/www.psyctc.org\/psyctc\/wp-json\/wp\/v2\/doc_category?post=2650"},{"taxonomy":"doc_tag","embeddable":true,"href":"https:\/\/www.psyctc.org\/psyctc\/wp-json\/wp\/v2\/doc_tag?post=2650"},{"taxonomy":"glossaries","embeddable":true,"href":"https:\/\/www.psyctc.org\/psyctc\/wp-json\/wp\/v2\/glossaries?post=2650"},{"taxonomy":"knowledge_base","embeddable":true,"href":"https:\/\/www.psyctc.org\/psyctc\/wp-json\/wp\/v2\/knowledge_base?post=2650"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Try also<\/h4>\n\n\n\n
Estimates and estimation<\/a>
Gender categories (in quantitative research)<\/a>
Internal vs<\/em>. external analyses<\/a>
Precision<\/a>
Referential data
Statistical power<\/a>
Validity<\/a><\/p>\n\n\n\nChapters<\/h4>\n\n\n\n
Dates<\/h4>\n\n\n\n