China girl, pt. 4: the structural mechanisms of exclusion - how we designed women out of defense, then refused to measure what we'd done
Or: how veteran hiring pipelines, security clearance financial vetting, corporate consolidation, and a comprehensive research void became the institutional architecture of a $100 billion annual loss
Part 1, Part 2, and Part 3 of the China girl series established what America loses by excluding women from defense technology: China’s 10x drone advantage, their 13-month closure of AI capability gaps, their 5-6x faster weapons acquisition, and our $100 billion in annual economic losses compounding to $4.5 trillion since 1976. We’ve documented the hemorrhage - 10,000-13,000 female engineers lost annually, 70,000 positions sitting empty while 275,000 qualified women remain excluded.
But how does this exclusion actually happen? It’s not enough to observe that defense is 23% female while China mobilizes 46% of their technical workforce. We need to examine the specific institutional mechanisms that create and maintain these gaps while preventing any evidence-based reform.
Part 4 identifies four structural barriers that aren’t accidents of history but active design choices embedded in policy, hiring practices, and institutional culture: the veteran hiring pipeline that imports military demographics and culture wholesale, the security clearance system that treats educational debt as a security vulnerability, the 1993 consolidation that erased 2 million jobs without measuring gender impact, and the comprehensive research void that prevents us from even identifying which barriers matter most.
Part 4’s subsections:
1. The veteran hiring pipeline and the culture it imports
2. The ouroboros known as the security clearance system
3. The consolidation that erased the evidence
4. The research void that prevents reform
Here I’ll examine some specific institutional barriers that create and maintain gender gaps in American defense while preventing any evidence-based reform.
Key points:
Veteran pipeline: 82% male military flows directly into defense hiring, and disparity imports problematic aspects of institutional failures
Security clearances take on average 249 days wait with financial reviews that punish student debt (women carry 58% more)
1993 consolidation of defense contractors meant 2M jobs lost, but zero gender impact analysis conducted
Research void - there is no demographic data in clearance processing nor of defense roles post consolidation from a gender perspective
Photo by Cheng Shi Song on Unsplash
The veteran hiring pipeline and the culture it imports
Defense contractors prioritize veteran hiring for legitimate reasons - veterans have clearances, understand chain of command, and have proven they can handle high-stakes work under pressure. The policy makes operational sense and honors service. The problem is not the policy itself but what it statistically produces when left unexamined, which is how this leads to forming one structural mechanism excluding women in defense tech.
The military is 82% male, defense contractors prioritize veteran hiring, and in 2018, RAND found veteran hiring preferences are the single largest driver of gender gaps in defense employment. Since most veterans are men, these policies create what RAND delicately calls “the possibility of a trade-off” between veteran hiring and gender diversity. The possibility is doing a lot of heavy lifting here, as if it’s not mathematically obvious that recruiting heavily from an 82% male population will produce an 82% male workplace. No one wants to acknowledge this dynamic out loud because any critique of outcomes gets misread as critique of veterans themselves, which is career suicide in defense, and the pipeline problem remains undiscussed while workplace culture reflects the demographics it imports. Foundationally, it imports institutional norms developed for military operational contexts where unit cohesion under existential threat requires hierarchical authority that cannot be questioned and aggressive male bonding rituals that build combat effectiveness. Those cultural mechanisms serve their purpose in military contexts but they create problems in varying contexts within the defense industry such as in engineering where the work requires dissent, collaborative problem solving, and integration of diverse technical perspectives. Defense technology development requires people to question assumptions and push back on flawed approaches even when leadership is committed to them, but that’s easier said than done. When you import military cultural norms that treat technical pushback as insubordination rather than due diligence, you get worse engineering outcomes in addition to the toil on morale.
Sexual assault statistics compound this. RAND estimates one in 16 active-duty women experiences sexual assault annually. One in four faces sexual harassment. Among women who report assault, over 60% face retaliation, usually from their own chain of command.
When these are the current baseline conditions in the institution that serves as the primary talent pipeline, what transfers is not the assault rate itself but the institutional norm that you do not report problems up the chain because reporting makes you the problem. Reports about women’s experiences at defense contractors have described it as a “male party mentality” where advancement required joining the boys’ club or suffering in isolation. Recall the statistic from earlier in this article which found 83% of women in cleared professions reported witnessing or experiencing gender discrimination? It’s just one of many facets to the issues which require addressing in American defense.
The structural exclusion of women in defense technology through veteran hiring pipelines is not an indictment of veterans or their service. It is an indictment of defense contractors who import military institutional culture wholesale without recognizing that the cultural mechanisms optimized for combat effectiveness actively undermine the collaborative problem-solving required for engineering work. The result is a defense industrial base that excludes qualified talent, suppresses technical dissent, and produces worse outcomes while wondering why China is closing capability gaps faster than our models predicted.
The ouroboros known as the security clearance system
Another mechanism leading to the exclusion of women in defense has to do with stalled security clearance processing, which reminds one a lot of the ouroboros, an ancient symbol you’ve seen somewhere before, it’s the one of a snake eating its own tail, which is what the security clearance system in the U.S. parallels.
Dear reader, did you know the average time for a Top Secret clearance is 249 days? That’s over eight months of bureaucratic limbo. For a 29 year old woman with a fresh PhD weighing career trajectory against fertility timing, that waiting period becomes a biological tax her male peers don’t face while her classmates at Google or Meta started work the week after graduation (which was not in this economy, that’s for sure). Our newly minted PhD is sitting, waiting, wishing while her student loans accrue interest and her professional network moves on without her as the security clearance process drags on…and on…and on. Even more pressingly, the financial review component of the clearance process makes it all the more aggravating, as financial issues are also the top reason for clearance denial at 29% of cases, as analyses of adjudication decisions consistently find “financial considerations” are the single most common basis for clearance denial or revocation.
Women hold roughly two-thirds of U.S. student loan debt despite being just over half of college graduates, and Black women carry the heaviest balances of all. Women also take more career breaks for childbearing and earn less for the same credentials. This means the clearance process’s “financial risk” screen lands on women more often, even though we have zero evidence that women with debt are more likely to sell secrets. We are literally screening out people for getting educated while not being rich, which reflects a system that treats the consequences of systemic inequality as individual security vulnerabilities. A woman who took out loans to get the engineering degree we claim we desperately need becomes a risk factor, while the guy whose parents paid for his education sails through this part of the process. The policy mistakes wealth for trustworthiness and debt from education for vulnerability.
Now, of course, it makes sense on paper to think that financial stress creates security risk through coercion, vulnerability, bribery, blackmail, etc. yet the fundamental problem with financial vetting as currently implemented is that it privileges the role of money disproportionately compared to other factors. Intelligence community research doesn’t support that level of confidence. The Central Intelligence Agency’s Project Slammer amongst others in decades of case studies shows spies have been driven by messy cocktails of ego, grievance, ideology, and sometimes money - not always, but sometimes! This means there is not a neat correlation between a credit score and betrayal, and actual espionage cases reflect the ways money concerns show up as motivations for bad faith actors. Aldrich Ames literally walked into the Soviet embassy in 1985 asking for $50,000 to pay off his debts and went on to collect millions and Robert Hanssen was hundreds of thousands of dollars in the hole while spying for cash and diamonds. Yet the clearance system isn’t catching future Ameses by screening for student loan balances, it’s just procedurally hammering anyone whose finances reflect structural inequality rather than bad judgment. A more contemporary reminder would be Edward Snowden, who wasn’t in financial distress (Booz Allen Hamilton said he earned about $122,000 a year), yet he still torched his career and freedom over ideological objections to mass surveillance. People do all sorts of things for all sorts of reasons, and the security clearance isn’t always going to pick up on it. The people who become security threats are motivated by complex combinations of ideology, ego, disgruntlement, or moral objections and not just always sheer simple financial desperation that would show up in a credit check. Meanwhile the policy systematically excludes people with financial challenges who would never consider espionage but happen to have student debt, career breaks, or pay gaps creating financial stress.
The consolidation that erased the evidence
In 1993, facing post Cold War budget cuts, Defense Secretary Les Aspin told contractor CEOs to consolidate or die. I suspect that they had the good sense of knowing what happens at the end of the first Godfather film if they didn’t comply, so the defense contractors listened. The industry shrank from 51 major contractors to 5 and employment went from 3.2 million to 1.1 million. Two million jobs vanished, and nobody tracked gender impacts.
Not at the Department of Defense. Not at the contractors. Not at the Government Accountability Office. Stunningly, not even the academic researchers (did this not occur to anyone for a PhD? People! Niche of niches! C’mon, in the style of Gob Bluth). Millions of jobs evaporated from defense and we have zero data on whether women were disproportionately cut - we know about cost, competition, and supplier risk analyses, but we have no published gender impact evaluations for that 1990s wave.
As such, we can infer what happened because we have data from every other industry consolidation. Women get fired first and hired back last. A Columbia study found female managers face 65% greater rank drops than men after mergers and see larger pay cuts even when controlling for performance
In tech consolidations, women are twice as likely to be cut. In finance, the disparity is even worse as industry‑specific merger studies and labor‑economics reviews consistently find women disproportionately affected by layoffs and demotions in M&A across sectors.
During the biggest restructuring in defense industry history, women almost certainly took disproportionate hits. We just didn’t bother to check, which tells you how much defense valued gender in 1993, meaning not enough to even count what we lost. While culture wars are fought with words nowadays, I prefer to stick to data and what we can learn from it to find solutions, which so the timing makes this failure more damning.
During this same period, commercial tech began its diversity push. By the 2000s, major tech companies averaged 29 to 45% women while defense went the opposite direction. Lockheed went from 16% to 19% during the consolidation, with women forming about a quarter of employees at the top five U.S. defense contractors overall. The industry restructured completely and somehow got less diverse. This was not inevitable. It was a choice, or more accurately, it was the result of not choosing to measure or care about gender impacts during the largest workforce restructuring in defense history.
The research void that prevents reform
These structural barriers persist partly because we have almost no rigorous research examining how defense industry mechanisms differentially impact women. While general diversity issues in defense are documented and military gender integration research is robust, peer reviewed studies specifically on defense contractors remain remarkably sparse. This absence prevents evidence based policymaking and perpetuates barriers through lack of visibility - there is literature on gender in the uniformed military and in general workplaces, but far fewer peer‑reviewed studies focusing on civil defense contractors as such. Even RAND’s notes that the security‑clearance process and vetting pipeline have not been systematically evaluated for demographic bias, and they have a ton of funding. I just have coffee and willpower. We are not the same!).
The research gaps are comprehensive, to say the least.
There is no demographic data collected during security clearance processes, which prevents identification of gender disparities in outcomes.
There is no gender analysis of the 1990s defense consolidation wave despite 2 million job losses.
There are no empirical studies on how compartmentalization affects women’s professional networks,
There is no quantified data on whether procurement cycle volatility affects women’s retention differently.
There is no comparison of defense versus commercial tech sector retention controlling for credentials and experience.
If I continue to say no and type it one more time, frankly, I may as well become French.
There is no - scratch that, this is not an accident. You cannot fix problems you refuse to measure, which is why the absence of research is itself a structural mechanism of exclusion. Without data, we cannot identify which barriers have the largest impacts. Without studies, we cannot evaluate which interventions might work. Without measurements, there is no accountability for failure. The research void ensures that gender gaps in defense can be attributed to anything except the structural mechanisms that actually produce them. It allows defense contractors to shrug and claim they just cannot find qualified women while ignoring that their own systems are designed to exclude them.
Concluding remarks and looking ahead to part 5:
These aren’t four separate problems. They’re four facets of the same structural reality: American defense has built institutional mechanisms that systematically exclude women, and then refused to measure whether those mechanisms work.
The veteran pipeline prioritizes an 82% male source population without considering alternatives. The clearance system punishes financial circumstances that correlate with gender while lacking evidence that debt predicts betrayal. The 1993 consolidation cut 2 million jobs without checking if women bore disproportionate losses. And the research void ensures we never gather the data that would force us to confront any of it.
China doesn’t have these barriers. Their Military-Civil Fusion doctrine treats every technical worker as defense-relevant from day one - no clearances, no financial vetting, no waiting, no choice. While we’ve built elaborate systems to filter people out, they’ve built systems to pull people in.
The structural mechanisms examined here explain why qualified women leave engineering at 2.5x the rate of men, why 40% exit the field entirely, why defense can’t fill 70,000 positions while excluding 275,000 qualified women. These barriers aren’t natural or inevitable. They’re policy choices we’ve made and then defended by refusing to study their impacts.
Part 5 will prove this isn’t unsolvable. We’ve actually done this before. During World War II, we mobilized women to become 80% of our codebreakers. During the Apollo program, women were the computers who put us on the moon. We have historical proof that integrating women into defense technology works. We just forgot while China took notes.