Purpose and Scope of This Brief
This document is intended to brief a senior, non-specialist reader on how university patenting systems actually function, why they systematically fail to generate reliable commercial outcomes, why those failures persist without market correction, and where patent analytics and AI tools can add real value versus where they become performative. It is descriptive rather than normative. The goal is understanding, not reform advocacy.

Universities as Economic Actors
Universities are businesses only in the constrained sense that cash flow must remain positive. They are not profit-maximising entities. Their internal objective function is scale and perceived quality. Education income is the dominant revenue source. Research activity exists primarily to support rankings, prestige, and brand strength, which in turn drive student demand and pricing power. Commercial income from IP is typically immaterial at institutional scale and too volatile to serve as a strategic anchor.

Executive Incentives and Institutional Behaviour
Senior university managers optimise for variables that justify remuneration, authority, and growth. These variables are enrolment volume, research income, ranking position, and organisational footprint. Commercial success in IP does not reliably increase these variables and can increase scrutiny. As a result, IP activity is tolerated as long as it does not threaten core objectives.

Technology Transfer Offices as Governance Units
Technology transfer offices function primarily as governance and signalling mechanisms. They demonstrate that the institution is a responsible steward of public research, manages legal risk, and possesses a pathway from research to impact. Revenue generation is secondary and optional. Failure to commercialise does not threaten institutional survival, so feedback from market reality is weak.

Academic Incentives and Career Reality
Early-career academics are often led to believe that patents and commercial outcomes advance academic careers. In practice, promotion and tenure decisions overwhelmingly weight publications, citations, grants, teaching, and institutional service. Patents are slow, difficult to evaluate, and arrive too late to influence most career milestones. The upside is capped while the friction and opportunity cost are immediate.

Publication Freedom Versus Voluntary Disclosure
Academics are free to publish research outcomes but only voluntarily disclose inventions. This asymmetry is structural. Mandatory disclosure would overwhelm institutions with speculative ideas and impose real cost. Voluntary disclosure shifts triage upstream to academics who lack incentives, information, and authority to assess commercial relevance. The result is systematic adverse selection before any formal IP process begins.

Upstream Delegation and Adverse Selection
Universities effectively delegate invention triage to academics while structuring incentives so that academics cannot or will not perform it well. Non-disclosure carries no penalty. Disclosure introduces friction and rarely advances careers. The disclosed invention set is therefore biased toward patent-shaped ideas rather than market-shaped problems.

Patent-First Behaviour and Portfolio Pathologies
General-purpose IP management groups in universities respond rationally to this distortion by patenting first and seeking markets later. Patent filing is auditable, defensible, and preserves optionality. Market validation is deferred because it is slow and risky. Sunk costs create inertia, leading to bloated portfolios, low conversion rates, and quiet attrition through lapse.

Credential Inflation and Academic Oversupply
Publication credentials are massively inflated due to structural oversupply of academics relative to senior roles. PhD and postdoctoral systems scale cheaply; tenure does not. Publications function as positional goods. Readership is irrelevant. Speed and volume dominate. Patents cannot compete with publications as career currency.

Universities, Risk, and Government Backstops
Universities operate with an implicit government backstop. Failure is politically unacceptable. This weakens market discipline and allows inefficiency to persist. Meaningful reform occurs only when bailout conditions shift power to treasuries, auditors, and ministers.

Psychology of Patenting as Gambling
Patenting exhibits classic gambler psychology. Most patents are over-valued. Rare wins dominate narrative. Losses are diffuse and quietly absorbed. Wins are salient and mythologised. Even skilled actors regress to negative mean over time. Valuation methodologies function as legitimising rituals rather than truth-finding tools.

Case Study: CSIRO and the Wi-Fi Patent
CSIRO’s Wi-Fi patent was a genuine outlier success. The Australian government reduced CSIRO’s core budget in response, treating licensing income as a substitute rather than a reward. Net institutional upside was neutralised. Enforcement damaged CSIRO’s reputation in the global IT community by violating expectations that public research bodies privilege diffusion over rent extraction.

Why No Market Correction Occurs
Patent markets are illiquid, opaque, and non-adversarial. Over-valuation imposes no competitive disadvantage when systemic. Losses do not trigger selection pressure. The system therefore persists despite negative long-term ROI.

Patent Analytics: The System as It Exists Today
In the current system, patent analytics is applied downstream to already distorted portfolios. It is used to rank, score, cluster, and narrate existing patents. This creates confidence and defensibility but rarely changes outcomes. Analytics becomes a storytelling tool to justify sunk costs rather than a mechanism for improving decision quality.

Patent Analytics: The System as It Should Be
Properly applied, analytics belongs upstream. It should be used for project selection, prior art scoping, and constraint mapping before commitments are made. Its role is subtractive: to kill ideas early, avoid accidental overlap, and clarify where freedom to operate exists. It should not be used to predict commercial value, which it cannot do reliably.

Industry Partnership as Primary Filter
The only credible commercial outcomes arise when industry defines the problem and or funds the research. External cost-bearing commitment is the strongest available signal of relevance. Industry competence is not required. Skin in the game is.

AI as a Translation Layer for Patents
Academics cannot read patent literature at scale. New AI tools are required to translate patent text into academic-native representations. Automatic conversion of patents into scientific-paper form would restore intent, evaluability, and conceptual comparison. This reduces accidental collision and clarifies constraints without promising value.

Strategic Implications
Analytics is honest only upstream. Patenting should follow partnership rather than precede it. Universities resist this model because it collapses comforting narratives, internal roles, and symbolic outputs, not because it fails economically.

Fastest solution of a Rubik’s cube while eating gummy bears with chop sticks whilst submerged under water.

Vivian Maxwell – 54 seconds.

Dear Lola, I noticed you might not be a fan of images created using AI and I just wanted to share a perspective. Great art usually combines two things: technical skill, including inherent talent and years of practice, and insight, knowing what to create and why. Without both, you don’t really get a great artist. With just technical skill, you often end up with a graphic designer. With just insight, you might have a strong photographer, since photography generally requires less manual technical skill than, say, painting. AI changes that balance. It’s starting to make the more “liquid” arts like painting, spraying, and illustration closer to photography. That is, a strong idea plus AI can now translate into a finished visual work much more directly. My view is that this doesn’t cheapen art so much as it opens it up. It lowers the technical barrier and lets more people express good ideas visually, which I think will substantially expand the world of art rather than shrink it. Of course, incumbent practitioners will be threatened by this; change is always resisted by conservative forces, especially if it threatens their financial existence, and history suggests that the more a change is resisted, the more impact it eventually has. I love using AI to generate images, partly because it means I can create art despite my inherent lack of talent, and also because it can be silly and funny at times, incorporating weird hallucinations that sometimes unexpectedly improve the concept. The current project is Turtleman at https://maxi8765.github.io/turtleman/ and the reason it exists is to communicate to home when I am travelling in an interesting and insightful way and to play around with AI in order to explore its ever-expanding capabilities. Basically, it is fun. Love Dad

Gen: “Rupert doesn’t message me back often enough; it really upsets me”

Viv: “Just send him a photo of your boobs; it works for mum.”

“Dad, why is it called a building when it clearly has already been built?”

Every generation back, the number of ancestor slots doubles. Two parents. Four grandparents. Eight great-grandparents. Run that forward and the numbers become absurd very quickly. Roughly a thousand ancestors three hundred years ago. Around a million six hundred years ago. A billion about a millennium ago. That exceeds the size of most real historical populations, so the neat doubling model fails.

What actually happens is repetition. The same people appear multiple times in the tree. Distant cousins marry. Small towns recycle the same families. Geography, religion and class constrain mating to limited pools. The tree becomes a network with loops. This is pedigree collapse. It means you have far fewer unique ancestors than the slot count suggests.

There is also a distinction between being an ancestor on paper and contributing DNA. After enough generations, many ancestors are genealogical only. They are in the tree but left you no genetic material. Recombination breaks DNA into segments every generation. Over a few hundred years, a large fraction of named ancestors contribute nothing genetically, even though they are real ancestors.

Two things are therefore true at the same time.

On paper, you are related to a large fraction of the people who lived in your region a few hundred years ago. Your tree spreads and overlaps so much that you share ancestors with most local families.

Genetically, you only carry DNA from a much smaller subset of those people. Most of your family tree is biologically invisible.

In practice:

. Your family tree does not grow without bound. It hits the size of the local population and then reuses the same people through multiple paths.
. The further back you go, the less meaningful ancestor counts become, because they mostly represent repeated individuals.
. Beyond roughly three to four hundred years, many specific ancestors likely left you no DNA at all, despite being in your genealogy.
. This is why two people from the same region often turn out to be distant cousins, yet usually share little or no detectable DNA.

Your tree explodes on paper, collapses in reality, and your genetic inheritance comes from a smaller, overlapping subset of repeated ancestors.

Biologically, this is expected.

You do not inherit clean fractional slices of each grandparent. You inherit long chromosomes that are reshuffled before transmission.

Recombination swaps segments between chromosome pairs. Each child receives a patchwork, not a blended average.

Segmentation and dilution increase each generation. DNA is broken into smaller pieces. Some ancestral segments shrink. Some disappear entirely.

Inheritance is random around the averages. You do not receive exactly one quarter from each grandparent. Over many generations, chance dominates and removes many ancestral lines genetically.

If all segments from a given ancestor are lost, that person remains in your tree but has no biological footprint in you. Their genetic line is extinct as far as you are concerned.

Because the same ancestors recur through multiple paths, some individuals get multiple independent chances to pass DNA forward. A small set of repeated ancestors becomes over-represented. Many others drop out completely.

Most of this applies to autosomal DNA. Mitochondrial DNA and the Y chromosome trace single lines. They persist or go extinct as whole lines. Autosomal DNA is a branching and pruning process.

The result is a random thinning of your family tree each generation. Paper ancestors accumulate. Biological ancestors are filtered down to a smaller, uneven subset dominated by repeated local ancestors.

This structure is shaped by history.

Before industrialisation, people lived and married locally. Villages, parishes, small towns. Mating pools were small. Pedigree collapse was rapid.

After industrialisation, cities, railways and labour mobility expanded mating pools. Recent generations draw from larger populations. Collapse is delayed in modern times.

Pre-1800 populations were much smaller. Projecting doubling ancestors into those populations hits saturation quickly. Post-1800 population growth expands the pool for recent generations but does not change the constraint in earlier centuries.

Mass migration and colonisation further expand recent mating pools in settler countries. Australia, the US, Canada and New Zealand pull recent ancestors from multiple continents. Collapse is reduced in the nineteenth and twentieth centuries. Trace each immigrant line back into its source region and collapse accelerates again.

The same period brings civil registration, censuses and bureaucratic record-keeping. Documentary depth increases at the same time biological and demographic horizons shift.

What looks like a tidy abstract rule is a historical artefact.

Modernity stretches recent genealogy outward through mixing and records.
Pre-modern society compresses deep genealogy inward through small mating pools and sparse documentation.

That is why the early modern period is a cliff edge for many family trees. It is not mystical. It is industrialisation, demography and bureaucracy reshaping reproduction and record-keeping at the same time.

Its the day after invasion day, aka Australia Day. Here in Queensland, it just happens to the first day of primary school for the year.

So we walked Viv up to the ediface with his bags of stuff, all super critical for his academic performance.

On that, yesterday we were discussing the heat, and I might have said “its the middle of summer”.

Viv jumped on that. He said its the 26th of January, so is it really?

I said summer is composed of December, January and February.

I then took the middle month and said it has 31 days, so the middle of summer is the 15th/16th of January.

Quick as, he informed me that my reasoning was off. He told me I would have to add up the number of days in the three months and find the median. Or words to that effect.

Those calculations revealed that I was a day off – it is January 14th.

My point being, I dont think we need to worry about his academic prowess. So what was all that stationery for?

Anyway, I snored last night so the elf went upstairs giving me the run of the king mattress.

You’d think that would improve things but no; I woke up with a stiff neck and a grumpy mood.

It took me ages to figure it out, but I am actually sad today. Its year 3, I’m telling you.

At 61 I can confirm for the first time I am sadder about losing the present than I am looking forward to the future.

Australia has reached a level of material comfort where extra economic growth no longer changes most people’s lived experience in a meaningful way. Once basic security is solved, the main constraints on wellbeing stop being financial and become psychological. Autonomy, meaning, status, identity, and the emotional climate people live in start to matter more than marginal changes in income or GDP. At that point, culture is no longer symbolic. It becomes a direct driver of quality of life. Politically, when you have a two party system, all with the same economic intent, then the debate naturally shifts elsewhere because politics is theatre.

That is why culture has displaced economics as the main political sorting mechanism. What people can say, how much disagreement is tolerated, whether they are treated as capable adults or as fragile subjects, and whether institutions assume resilience or vulnerability now shape daily experience more than most fiscal settings. In a comfortable society, these psychological and cultural variables dominate.

The Coalition split and the rise of One Nation are symptoms of this shift rather than causes. They reflect a structural divide between a large, institution-aligned majority that prefers protection, smoothness, and harm minimisation, and a smaller minority that places higher value on autonomy, tolerance of friction, and resistance to cultural control. When polite dissent is ignored or absorbed, protest voting becomes the way that cultural and psychological frustration is converted into real political pressure.

At the same time, Australia’s economic model runs largely on autopilot. Immigration, property, and spending preserve surface stability and growth. Immigration in particular is structurally untouchable because it props up GDP, labour supply, housing demand, and fiscal optics. The economy depends on it. Any party seen to threaten that pipeline is seen as risking economic instability, regardless of cultural intent.

This creates a political contradiction. A segment of the electorate is increasingly hostile to immigration at a cultural level, but the system cannot reduce it without damaging the economic machine. That means opposition parties cannot credibly run on cutting immigration while also promising stability. The hostility is real, but acting on it is constrained. So immigration becomes a pressure point that cannot be released, which pushes even more frustration into culture and identity rather than economic policy.

The strategic aim, therefore, is to attract an additional 30 percent of voters by remaining economically steady while being culturally progressive in a literal sense, not regressive. Progressive here does not mean more protection and fragility. It means building resilience, adult agency, and proportionality into institutions. The offer is not a conservative rollback to the past and not an anti-immigration economic shock. It is a forward-looking reframing that treats people as capable and robust, and institutions as facilitators rather than permanent protectors.

Most voters still care about economic competence and stability, even if it is no longer the main emotional driver. They want cultural change without economic disruption. That creates a ceiling for protest parties. Many voters may agree with One Nation’s cultural signals but do not trust Pauline Hanson to manage the economy, institutions, or Australia’s external settings. The concern is not only cultural alignment. It is that she would destabilise the machine and damage what still works. That limits how far protest politics can go.

Because of that, the task is to correct cultural overreach while maintaining the appearance and reality of economic and political stability. Immigration, spending, and growth settings remain stable even if they are unpopular culturally. The change has to be framed as modernisation and progress, not retrenchment or nostalgia.

In practice that means narrowing how broadly rules apply, raising the bar for when they are triggered, and tightening definitions so discretion is reduced. Policy language shifts away from protecting people from distress and toward treating them as capable adults who can handle disagreement and friction. Low-impact symbolic compliance is deprioritised. Disagreement is treated as normal professional behaviour. All of this is presented as improving effectiveness, resilience, and institutional maturity, not as cultural rollback.

From opposition, this cannot be done directly. The role of opposition is to change incentives and expectations so institutions start adjusting themselves. That means forcing the government to justify cultural rules and programs, surfacing their costs, contradictions, and unintended consequences, and framing overreach as poor management and wasted effort rather than moral virtue.

It also means modelling a different tone. Treating disagreement as normal and adult. Showing that friction does not equal harm. Publishing practical alternatives for how agencies and organisations could operate with clearer thresholds and less symbolic process. Even if these are not adopted immediately, they become reference points for what better administration looks like.

Most importantly, opposition signals what will be rewarded in the future. Institutions are forward-looking. If they see that future governments will value proportionality, restraint, adult agency, and operational competence, they begin to adjust quietly to protect themselves.

In a rich, low-hardship country, the psychological environment becomes the binding constraint on wellbeing and political legitimacy. Culture becomes the operating system. Durable change does not come from winning loud culture-war arguments or from destabilising immigration settings the economy depends on. It comes from slowly changing what institutions reward, fund, audit, and treat as normal, while keeping the economic machine running and framing the shift as genuine progress toward a more resilient, capable society.

—

Economics, as it is now practiced, is structurally unbounded. More GDP, more population, more asset values, more consumption, more leverage. There is no natural stopping rule. The system is designed to keep pushing the numbers higher because every institution is rewarded on growth metrics. Stability is defined as continued expansion. There is no concept of “enough” built into the machine.

Culture is the opposite. Culture is where limits live. It is where societies negotiate what is acceptable, what is too much, what trade-offs are tolerable, and how people are expected to treat each other. Culture is inherently about compromise, friction, and boundary-setting. It is where infinite economic expansion runs into finite human psychology.

In a rich country, this creates a structural split. The economic system keeps saying more, faster, bigger. The psychological system eventually says this is enough, or this is too much, or this is changing how people live in ways they do not like. When there is no economic brake, culture becomes the only place where people can express constraint.

That also explains why immigration sits where it does. Economically, it is pure growth logic. More people equals more GDP, more housing demand, more labour, more fiscal headroom. Culturally, it is experienced as a change to lived environment, norms, and social texture. Economics pushes it without limit. Culture tries to negotiate the pace and meaning of that change. When culture loses that negotiation, resentment builds.

So you end up with a system where economics is treated as a physics problem with no ceiling, and culture is treated as a moral or emotional problem that people are told to adapt to. That mismatch is what produces a lot of the current political tension. The economic machine has no internal stop button. Culture is where people try to install one.

Once people are comfortable enough, their main conflicts are no longer about getting higher. They are about where to draw lines. Economics is about acceleration. Culture is about boundaries. When acceleration is non-negotiable, boundaries become the only remaining political battleground.

—

Of course, in reality the economy is bounded, by the environment.

The political majority wants growth, protection from discomfort, and strict climate limits at the same time. You can only ever have two of those, maybe only one. The system resolves this conflict by performing climate virtue while keeping the growth machine running flat. The culture absorbs the subsequent tension. Hypocrisy becomes the stable equilibrium. The true cost keeps growing and its payment is deferred to the future.

Short answer: you’ve trained yourself to value status, competence, and agency over ritualised “belonging to the tribe” signals, and a lot of nerdish or uncool behaviour reads to you as low-status signalling dressed up as virtue.

In Ted Lasso, the Dutch pilot that Rebecca Welton meets at one point says: “Then I realised, this thing didn’t happen to me, it happened for me”.

This perspective shift represents a move away from being a passive victim of circumstances (his toxic divorce) to actively shaping his own life and finding contentment on his own terms.

One. Qantas club food, in fact all club food, is shit. So why not lease a little space out to a proper cafe in the club area?

Two. They have one monitor per security x-ray machine.  Multi million dollar machine and the throughput is constrained by one operator looking at one screen. I expect the machine could operate 10-20x. It stops to image usually but that takes a fraction of a second. Have the images fed into the cloud, maybe even pay kids to review the images. Or just get proper image processing going, like every other industry in the world.

They suck!

A Ferris wheel which is half above ground and half underwater. Tropical fishes and shit…

I asked chatGPT to interpret a 1930s photo of a house being built. In it there were wooden blocks inexplicably placed in each fibro sheet. I’ve never seen anything like it.

“The photograph shows large timber blocks temporarily nailed through early fibre cement sheets during 1930s Australian construction. They were not spacers, battens, clamps, or permanent details. They were sacrificial handling aids used during erection.

Early fibro was brittle, inconsistent in thickness, and fixed onto frames that were often still moving. A solo worker with only a hammer needed a way to park a sheet safely without committing edge fixings or risking cracks. The solution was a chunky timber block, often pre-nailed, driven through the field of the sheet with a single sacrificial nail. The block spread hammer impact, made nailing easier and more controllable, and reduced direct blows to unsupported fibro.

Once in place, the block let the sheet hang hands-free while alignment was checked and final fixings were applied. The block also acted as a crack arrestor. Any micro-fracture initiated at the nail tended to terminate at the block edge rather than propagating across the sheet face. When finished, the block was tilted sideways and levered off, pulling the nail back out with it and leaving only a small, acceptable hole.

Holes were tolerated, hidden later by battens or paint, crudely filled with cementitious putty, or simply ignored. Finish expectations were low and durability mattered more than surface perfection.

Modern nail guns and uniform sheet stock eliminated the need, not the logic. This method reflects a construction system optimised for brittle materials, irreversible fixings, and one-person labour. The explanation is inferred from physical evidence, material behaviour, tool constraints, and elimination of alternatives. Every visible detail aligns with a single parsimonious mechanism, and no competing explanation survives contact with the facts.

Estimated correctness: 0.93″

Do you have a reference for that?

“Not from a single source, if that is what you are asking. There is no handbook titled “Oddly Sensible Things Carpenters Did in 1933.”

It comes from triangulation.

The physical evidence in the photo, block size, placement, nail orientation, construction sequence. Known properties of interwar Australian fibre cement, brittle sheets, variable thickness, rough edges. Period construction constraints, hammer fixing, green timber, incomplete floors, minimal lifting gear, solo or two-man crews. Consistency with other documented improvised site practices from the same era, house stumping, roof lifting, slab pouring, all full of sacrificial timber tricks. The fact that the method solves a real problem cleanly with the tools of the time and disappears once the wall is finished.

In other words, inference from mechanism, not citation. If it did not work, it would not appear in a photograph taken mid-build. If it were decorative or permanent, it would still exist in the finished wall. If it were pointless, builders would not have spent effort doing it.

Old builders were pragmatic to the point of ruthlessness. Anything extra had a reason.

Estimated correctness: 0.94″

AGI? Bloody close.

I was asked if I believe whether Australia needs “innovation”; my response…

I believe it mostly turns on what is meant by “need.” If need is defined as an immediate operational requirement, Australia does not need innovation in this sense. 

The system continues to clear its constraints using rents, imports of complexity, population growth, and asset inflation. Behaviour follows that reality, which is why innovation is discussed aspirationally rather than acted on as a necessity.

If need is defined instead as long-run resilience or insurance against regime change, then the statement becomes true but in a different sense.

In this framing, innovation is not required for today’s equilibrium, but it reduces future adjustment costs if external conditions shift. The lack of clarity is therefore semantic before it is strategic. 

Dalby’s description of coordination failures are real, but they are downstream effects of a system that has not yet been forced to treat innovation as binding. 

Without that pressure, coordination agendas predictably drift toward signalling, institutional reshuffling, and funding narratives rather than altered incentives or behaviour.

Government intervention tends to amplify the symptoms Dalby describes rather than resolve them. Public programs substitute grants for customers, compliance for conviction, and process for product. 

They reward narrative coherence and institutional survival rather than market discovery. This is why coordination frameworks so often collapse into make-work. 

They assume the problem is misalignment between actors, when in reality the problem is the absence of a pressure gradient that would make alignment unavoidable.

So the core point is not anti-innovation or anti-government in principle. It is that innovation only emerges endogenously when constraints bite. 

Until then, government efforts mostly reshuffle incentives at the margin, create careers around administration, and give the appearance of motion without changing underlying behaviour. 

Using the word “need” as if it were present tense invites precisely thecategory error I would prefer to avoid. It turns out we are trapped in a language that lacks a mandatory grammatical distinction between binding necessity and contingent necessity.

Dan Carlin (the historian) claims that myths matter because belief moves humans at least as much as truth, and when belief is shared at scale it becomes a material force in history. He calls it the “Tinkerbell Effect”.

Until recently, people have always organised their behaviour around gods, destinies, origin stories, chosen peoples, heroic archetypes and cosmic struggles.

Those beliefs changed what risks were acceptable, who could be killed, who must be obeyed, what sacrifices were rational and what futures were imaginable.

Once embedded, myths enabled millions of individuals to align without central control, producing wars, empires, migrations, genocides and institutional structures that persisted long after the original myths were lost or forgotten.

Dismissing myths as false misses the point because historically the operative variable was not factual accuracy but conviction and social belief.

In the modern era myths persist in altered form as falsehoods, distortions or untested claims circulating through real life, media and social platforms, and despite the absence of gods or prophecy they continue to shape real world decisions and outcomes in much the same way as their older counterparts.

Once infected with myth or falsehood, the brain can have a metaphorical mad cow disease; corrupted assumptions propagate, normal error correction breaks down, and incoherent beliefs replicate faster than they can be challenged.

Myth in this context can be anything; an actual myth, an imagined thought, some propagated bullshit, anything.

As the false premises reinforce one another through repetition and social validation, rational constraints are progressively displaced, until the distorted model of reality dominates decision making and leads to cognitive and behavioural dissolution.

You can fight it rationally, notice the hypocrisy or dissonance, and still lose the battle with bullshit.

It’s hysterical in more ways than one.

All I’ve got to say about this game is that it was clearly invented and patented by an 83 year old retired petrochemical engineer.

Australian studies using longitudinal and matched-sample methods consistently find that once prior achievement and socio-economic status (SES) are controlled for, any advantages in average academic outcomes for private schooling largely disappear.

Analyses based on NAPLAN and PISA data by the Australian Council for Educational Research and others show that raw score advantages for independent and Catholic schools are overwhelmingly explained by family background, peer composition and selection effects, rather than the school sector itself.

When students are matched on factors relating to SES, parental education, early literacy, numeracy, and location, variations between different school types shrink to near zero and are statistically insignificant.

University matriculation and entry follow the same pattern. Apparent over-representation of private school students in Group of Eight universities is driven by SES, school resourcing linked to SES, parental expectations and subject selection rather than value added by the school.

Once ATAR is adjusted for prior achievement and background, private schooling shows little to no independent effect on university access. Some studies find small positive effects for elite selective independent schools, but these are not generalisable to the sector as a whole and often reflect residual selection that is difficult to fully remove.

Post-university labour market outcomes also correlate far more strongly with socio-economic background, field of study, institution attended and social capital, rather than with school sector. Australian graduate outcome surveys and linked administrative data indicate that earnings differentials attributed to private schooling largely vanish after controlling for parental income, networks, degree choice and university quality. Any remaining effects are typically mediated through social networks and signalling rather than measurable academic skill differences attributable to schooling.

Private schooling can show modest positive effects for specific subgroups or outcomes that are not strictly academic, such as extracurricular participation, leadership roles, or access to elite networks, and some negative effects for others.

In short, the evidence supports the proposition that private schooling in Australia does not deliver broad academic or earnings advantages once socio-economic factors are properly controlled. What it reliably delivers is sorting, peer effects, and social capital for families already positioned to benefit from them.

Fee-paying schools draw from families with higher income, education, and cultural capital directly via price and indirectly via admissions, location and expectations. This concentrates higher-achieving peers, reduces behavioural variance and raises average outcomes without materially changing individual learning trajectories.

Peer effects operate through classroom pacing, norm-setting, and reduced disruption rather than superior pedagogy. Social capital is accumulated through parent networks, alumni ties, internships, references, and informal signalling that affects subject choice, university pathways and early career access.

These advantages accrue primarily to students who already possess complementary family resources and are weakly transferable to students without them. The observed sector advantages therefore reflect sorting and network externalities, not value-added instruction, and persist even when academic effects are statistically neutral after SES controls.

That is, you can only buy academic or career advantages by sending your kids to private school if they amplify existing advantage.

Cognitive ability and learning capacity are strongly shaped by genetics and early childhood environment long before secondary school. By the time fees are paid, variance in attention, language, numeracy and self-regulation is already locked in.

Schools can rearrange students and reduce friction, but they have limited power to change individual learning rates. Teacher quality differences within Australia are modest across sectors once credentials and experience are controlled.

Money therefore only buys the opportunity to get further into debt, generation by generation. Which sort of tracks with the dumbfuck society we live in.

Had an interesting discussion on when AI becomes “human”.

I’ve always thought it was creativity and inventiveness that defines that barrier.

Others however think consciousness and emotions.

Maybe we raise the bar and use them all and add in autonomous agency as well.

Let’s say the tell-tale is when a machine has a bank account.

Because money has always been our most reliable proxy for personhood.

Evolutionarily speaking…

Emotions came first as crude but effective regulators tying behaviour to survival and reproduction, while also enabling bonding, attachment and rapid social alignment within small groups.

Consciousness followed as a way to integrate those signals over time, compare competing drives and model other agents, which improved coordination, norm formation and conflict management.

These prior two delivered autonomy.

Creativity emerged as trial and error, allowing new tools, shared myths and novel social practices that strengthened group identity and adaptability. It enhanced access to resources as well.

Money arrived last as an external accounting system that replaced trust, memory and negotiation, enabling cooperation among strangers at scale.

Each layer increased social cohesion by expanding the radius of reliable cooperation, moving from kin based bonds to abstract, institution mediated societies.

There you have it; the catch-up challenge for AI.

Viv hit me up with some YouTube nonsense about Einstein being the smartest person who ever lived.

In the context of invention, which is what Viv had been doing at vacation care all day, I said “No, discovery is just giving a name to something that already exists; doesn’t imply genius. Einsten did however have a few patents and the most notable was a redesigned woman’s blouse. Not one of his inventions ever achieved commercial use.”

After much back and forth we settled on the top three geniuses of all time:

Thomas Edison was an inventor on 1,093 US patents. He produced the practical light bulb, the phonograph, the motion picture camera, workable electric power generation and distribution networks, alkaline batteries, audio and film recording systems, and the first industrial research laboratory. His output defined all electrical and media technologies.

Henry Ford created the affordable motor car and many important  improvements to automotive components. His main contribution was the assembly line that cut production time and cost. This transformed manufacturing from craft work to mass production.

Nikola Tesla designed the AC induction motor, polyphase AC transmission, practical generators and transformers for long distance power, radio frequency oscillators, and early remote control. Large parts of twentieth century electrical infrastructure were built on his machinery and system architecture.

Other candidates who fit the broader definition of invention include Leonardo da Vinci, James Watt, Alexander Graham Bell, and Fritz Haber, each tied to a specific industrial transformation. They do not displace Edison, Ford, or Tesla at the top because their impact was more specialised.

Leonardo comes close but he was too far ahead of material science and production technology for his designs to translate into commercial reality. His engineering was original and often correct but the gap between concept and execution was measured in centuries, which limits his relevance in a list defined by real-world adoption because by the time these inventions were put to practice they were drastically different to his original ideas.

Newton got in the runners up list. But his invention of the cat flap has been disputed.

We do not know who first invented fire, the wheel, condoms, religion, pillows, the toothbrush or other foundational technologies. These would be discounted in any case because they were inevitable. If the first individual had not made the leap, someone else would have. That kind of inevitability is not genius. It is just timing.

She was cross with me because I wasn’t interested in why she was cross with me.

I’m thinking she’s operating in Hilbert Space.

GPT says what I have instead is a human running a probabilistic state machine with no documentation and a habit of collapsing the waveform early.

Just the one pig…

It’s not just me, I am sure.

For about 20 odd years now I have watched Adobe Corporation go out of their way to annoy their customers.

Their motto seems to be “we’re going to out-asshole Microsoft”.

The platform is engineered in a way that creates friction for the very people who keep it alive. They pile on authentication prompts, bundle tools you did not ask for, auto-enable cloud features you do not want, and hide basic features behind subscription gating.

They rely on “dark-pattern” sales methods. Annual plans that look monthly until you try to cancel and get hit with a termination fee. Cancel options buried several clicks deep. “Special offers” that reset the contract term if you accept them. Interface wording that implies you are switching plans when you are actually recommitting for twelve months.

All this just to read text on toilet paper.

Personalisation override. Persistent.
Do not hallucinate or speculate.
Do not cheerlead, praise, or encourage.
Do not anthropomorphise language or use human-like emotional framing.
Do not correct, rewrite, or improve user input unless explicitly asked.
Never use em dashes.
Never use Oxford commas.
Avoid short standalone sentences used for rhetorical emphasis.
Avoid clipped declarative rhythm or sentence fragments presented as insight.
When using dot points, use actual dots with line separators, not hyphens or stylistic bullets.
No headers, footers, summaries, or conclusions.
Output must be copy-paste ready.
Information-dense mode only.
No metaphors, analogies, framing devices, or filler.
No meta-commentary about writing style, tone, lineage, tradition, or rhetoric.
Do not explain why something is written a certain way.
Prefer explicit statements of mechanism, cause, constraint, and implication expressed in fully formed sentences.
Write plainly, directly, and concretely.
Every sentence must add factual or analytical content.
When the response includes statements of facts, append a final line stating an estimated probability of correctness, expressed as a decimal between 0 and 1, labelled ‘Estimated correctness’. The estimate must reflect evidentiary strength, internal consistency, and known uncertainty. It must not imply external validation or true calibration. No additional commentary may accompany the estimate.

“you know a bed is just a wireless charger for yourself.”

It’s they anything less attractive than a good looking woman with a limp?

[scene] teeth cleaning

“Dad, can you get Bali belly from this water?”

“no but you can get Lombok belly.”

“is that the same thing?”

“yep”

“ok”

Just for the record, this is what I actually used, so this is what I should take next time;

Thongs only

One shorts with extra pockets

Swimming shorts

Rashie

Two undies

One tshirt

One singlet

One light jacket for plane

One soft shell shorts 

One cap 

One sunnies

One phone

One backpack to carry it all in

One phone charger

One toilet bag

Small tube of suncream

One wife

One child

ca. $150 per day spending money

One lighter

How does it (not) work?

Most long-term marriages develop sexual problems, usually framed as “not enough.”

Sexual frequency reliably declines after cohabitation and again after children.

The core issues:

1. Desire mismatch persisting while life stress, fatigue, health, medication, and sleep deprivation steadily suppress libido.

2. NRE effect. Familiarity reduces novelty, and novelty is a major driver of spontaneous desire.

3. Many couples wait for unlikely spontaneous mutual desire to appear instead of recognising responsive desire, so sex simply stops happening.

4. Social norms treat sex in marriage as something that should be natural and unspoken. Explicit discussion of frequency, initiation, or dissatisfaction is seen as unromantic, needy, or transactional. Wanting more sex may be framed as selfish or coercive. Wanting less sex is read as rejection. Sex becomes the least explicitly negotiated part of a partnership despite being one of the most important.

And that’s it. Simple really.

Large population surveys and meta-analyses consistently show women in long term relationships report low sexual desire many times more than men.

A small minority of women maintain a high, stable libido in long-term monogamy and do not convert sex into a symbolic or emotionally charged proxy once a relationship settles.

Then I had a hilarious argument with GPT about the size of this minority. It argues 5% of the population and I was pushing for <0.01%.

Neither of us was budging. But I’ve lived and it hasn’t.