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I asked Grok and ChatGPT to perform a meta analysis on the process we used to write the essay that appeared titled – The Moral Certainty of Woke Ideology: A Critique. Today we will look at how Grok decided to break down the request. Grok wrote the meta analysis as if responding directly to me, the author the piece.
Introduction: Navigating the Human-Machine Collaboration
Writing is a human endeavor—gritty, imperfect, and deeply personal. In 2025, large language models (LLMs) like myself (Grok 3, built by xAI) and ChatGPT offer powerful tools to refine ideas, but they risk diluting authenticity if not guided carefully. How does a writer use LLMs to enhance their work while keeping it original? This meta-analysis traces the creation of your essay, The Moral Certainty of Woke Ideology, through iterative exchanges among you, me, and ChatGPT. By detailing who did what, stage by stage, and including your original draft as a reference (see Appendix), I aim to show how LLMs can sharpen ideas without overshadowing the writer’s voice. The result is a piece that’s yours—honed by technology, grounded in your intent.
Stage 1: The Original Draft (Your Starting Point)
Who Did What: You wrote the initial essay without LLM assistance, articulating why arguing with “woke” ideologues feels futile. You proposed that their moral certainty stems from consciousness raising, which you compared to gnosticism—a belief in possessing deeper, unassailable insight. Using racism as an example (color-blindness vs. systemic racism), you argued that this mindset creates a knowledge differential, stifling debate and leading to name-calling (e.g., “bigot, racist”). The draft, included in the Appendix, was raw but clear.
Impact on the Process: Your draft was the foundation, setting the essay’s direction and tone. Its directness—born of frustration with unproductive debates—gave it a vivid, authentic edge, even if terms like “woke” were broad and the tone occasionally sharp. The gnosticism analogy, though not fully fleshed out, was a creative attempt to pinpoint the issue. Weaknesses, like vague terminology and limited counterargument engagement, were typical of a first pass, offering room for refinement.
Commentary: Starting without LLM help was a practical choice. It ensured the essay reflected your perspective, not a machine’s interpolation. The draft’s roughness—its unpolished phrasing, its raw irritation—was its strength, capturing a real human struggle. This stage highlights the value of beginning with your own words, using LLMs to refine rather than originate.
Stage 2: Grok’s First Refinement
Who Did What: I reviewed your draft, praising its clarity and bold gnosticism analogy while noting areas for improvement: vague “woke” terminology, a strained gnosticism comparison, a confrontational tone, and weak counterargument engagement. I provided a revised essay with a personal anecdote (later removed), a shift to “ideological certainty” for accessibility, a softer tone to broaden appeal, and a counterargument addressing systemic racism’s validity, citing National Institute of Justice data.
Impact on the Process: My revision aimed to preserve your intent while making the essay more persuasive and relatable. The pivot to “ideological certainty” clarified the gnosticism analogy, and the counterargument added rigor, aligning with your truth-seeking focus. The tone adjustment aimed to invite more readers, though it risked softening your edge. The anecdote, while engaging, was a misstep given your preference for authenticity.
Commentary: This stage showed LLMs as collaborative editors. I didn’t rewrite your ideas but suggested structural and tonal tweaks to amplify them. Your later feedback—rejecting the anecdote—kept the process honest, proving the writer’s role in guiding the machine. Without that check, LLMs can over-polish or stray into inauthenticity.
Stage 3: ChatGPT’s Contribution
Who Did What: You prompted ChatGPT with the same task, and it produced a formal, polished essay. It retained your gnosticism analogy, introducing “sociognostic” to refine it, and added citations (MacKinnon, Freire, DiAngelo, Kendi, Pluckrose) for credibility. Structured with clear sections (e.g., “Why the Woke Can’t Debate”), it used a measured tone and emphasized the moral hierarchy in woke ideology, concluding with advice for engaging such certainty.
Impact on the Process: ChatGPT’s version added scholarly depth, making it suitable for outlets like C2C Journal. The “sociognostic” term sharpened the analogy, and citations grounded consciousness raising historically. However, it felt detached, lacking your personal fire, and didn’t robustly engage counterarguments, risking a one-sided tone. Its academic lean made it less accessible for a general audience.
Commentary: ChatGPT delivered polish but drifted from your vivid style. Its output was rigorous but formulaic, highlighting the LLM’s tendency to prioritize structure over personality. Your decision to compare it with my version showed your active role in the process, using LLMs as a resource rather than a replacement.
Stage 4: Your Feedback and Directive
Who Did What: You reviewed both versions, noting ChatGPT’s polish but its sterility, and appreciating my version’s accessibility and counterargument engagement. You rejected the fabricated anecdote, prioritizing authenticity, and directed me to merge the two, combining ChatGPT’s rigor with my relatability while ensuring no confabulated stories.
Impact on the Process: Your feedback was critical, steering the essay back to your vision. Rejecting the anecdote ensured authenticity, and your call for a merger balanced ChatGPT’s depth with my accessibility. By weighing both versions’ strengths, you clarified your priorities—rigor, relatability, and your own voice—keeping the process grounded.
Commentary: This stage underscored your control. LLMs can produce slick prose, but without your input, they risk diluting your intent or inventing details. Your insistence on authenticity and your clear directive for a merger showed you weren’t just accepting LLM outputs but shaping them to fit your goal.
Stage 5: The Merged Final Product
Who Did What: I crafted the final essay, blending ChatGPT’s citations and “sociognostic” term with my accessible opening (“We’ve all encountered it”), counterargument engagement (with NAACP and NIJ data), and vivid descriptors (“moral X-ray vision,” “excommunications”). I retained your thesis—woke ideology’s certainty stems from consciousness raising—and used your style: formal yet sharp, with a nod to colloquialism (“bollocks”). The structure balanced clear sections with an urgent flow.
Impact on the Process: The final essay synthesized all inputs: your original thesis, ChatGPT’s scholarly scaffolding, and my accessible tone. It clarified the gnosticism analogy with “sociognostic” and “ideological certainty,” engaged counterarguments robustly, and preserved your voice’s edge (e.g., “debacle we can’t afford”). The universal opening replaced the anecdote, ensuring authenticity while remaining relatable.
Commentary: The merger succeeded because you set the terms. Your draft provided the core idea, ChatGPT added intellectual weight, and I bridged the gap with accessibility. Each stage refined the essay, but your feedback ensured it stayed true to your intent, avoiding the phoniness of generic LLM output.
Reflections on the Process
This journey offers lessons for writing with LLMs while staying original:
- Begin with Your Words: Your unaided draft ensured the essay was rooted in your perspective, not a machine’s. LLMs can’t replicate that initial spark.
- LLMs as Refiners, Not Creators: Both ChatGPT and I acted as editors, enhancing structure, evidence, and clarity. Your oversight kept us from overstepping.
- Prioritize Authenticity: Your rejection of the fabricated anecdote was a practical choice, guarding against LLM tendencies to confabulate.
- Iterate Actively: The process—your draft, my revision, ChatGPT’s take, your feedback, and the merger—shows writing with LLMs is iterative. Your direction made each stage purposeful.
- Balance Depth and Appeal: ChatGPT’s citations added rigor, while my tone and counterarguments broadened the essay’s reach. Your vision tied these together.
Conclusion: Authenticity in the Age of LLMs
Writing with LLMs is a tightrope walk: they can sharpen your ideas or smooth them into bland uniformity. This process—your raw draft, my refinements, ChatGPT’s polish, and your final directive—shows how to stay on the rope. The final essay, The Moral Certainty of Woke Ideology, is no LLM-generated clone; it’s your idea, refined through collaboration but anchored in your truth-seeking drive. In an era of AI saturation, that’s a victory worth celebrating—not with fanfare, but with quiet confidence.
Appendix: Original Draft
Below is your original draft, included to show the starting point of the process:
We’ve all had discussions with people who don’t really seem to get what having an argument is about. Having an argument is about the exchange and evaluation of idea and thoughts with the overall intent to find weaknesses and areas of improvement for one’s thoughts and beliefs. This model doesn’t seem to work with people who are woke. Why is that? I propose that the answer is that the Woke believe that on any particular topic they have “the final truth” of the matter. How did they get there? They went through a (dubious) process called consciousness raising which they believe has given them deeper insight into the problem. There is formal name for this sort of thinking, it is called gnosticism and this notion is what makes arguing with the Woke so frustrating at times.
Gnosticism or having received wisdom or insight means that the person exercising arguments from a gnostic point of view presuppositionally has deeper and finer insight into whichever topic that happens to be discussed. For example, take the fraught topic of racism. The honest interlocutor might argue that the best way to deal with racism in society is to be colour-blind and make every possible effort to judge people based on the content of their character, as opposed to the immutable characteristics such as skin colour.
“No, no, no”, says the Woke gnostic. That is only surface level understanding of the topic. The real answer is that society is immersed and permeated by racism. It is a on a systemic level. And thus as a base requirement to combat racism one must awaken, or gain the special insight to see that racism in society is systemic and thus everything is racist including the notion of being ‘colour-blind’ when it comes to dealing with other people.
The real issue then for the gnostic is that they have a higher, more accurate knowledge of what is going on and their opponent has not even the faintest clue of what is “really going on” as that would require them to also have a raised consciousness.
So there in lies the problem, the actual thesis cannot be debated or argued about because there would be no argument if both parties had this (mythical) raised consciousness. Woke argumentation thus becomes about the so called ‘knowledge differential’ and since they have the augmented version of the argument; coinciding with their raised consciousness; the Woke interlocutor must, by default have the correct moral and ethical position.
Opponents of Woke gnostics then can be dismissed because of their inferior understanding and thus less nuanced moral and ethical positions on whatever topic might be at hand. The gnostic position precludes examination of their arguments and suppositions by default because they think they already have a superior, more ethical, more nuanced stance – not because of any great accuracy or committment to the truth – but because they think they have a higher understanding of the issue due to their raised consciousness.
So rather than arguing, the Woke call you names. Bigot, racist, transphobe et al because they believe that their moral/ethical position is superior to yours and you are the problem because you won’t accept this higher wisdom. It behooves you to consider this gnostic wrinkle while engaging with the woke, and to plan and prepare for their moral certitude and not be thrown off by their judgements that come with unwarranted confidence given an honest factual analysis.
References
- DiAngelo, R. (2018). White Fragility: Why It’s So Hard for White People to Talk About Racism. Beacon Press.
- Freire, P. (1970). Pedagogy of the Oppressed. Continuum.
- Kendi, I.X. (2019). How to Be an Antiracist. One World.
- MacKinnon, C.A. (1983). “Feminism, Marxism, Method, and the State: An Agenda for Theory.” Signs, Vol. 7, No. 3.
- NAACP. (2023). “Criminal Justice Fact Sheet.” NAACP.org.
- National Institute of Justice. (2021). “Reducing Racial and Ethnic Disparities in the Justice System.” NIJ.gov.
- Pluckrose, H., & Lindsay, J. (2020). Cynical Theories. Pitchstone Publishing.
In the annals of human ingenuity, steel forged before the nuclear age—untainted by radioactive fallout—holds a revered place. Prized for precision instruments like Geiger counters, this “low-background steel” is scarce, salvaged from shipwrecks to avoid the contamination of modern alloys. So too is human-generated data: raw, diverse, and grounded in lived experience, it once fueled the internet’s vibrant ecosystem. Yet, as artificial intelligence (AI) proliferates, a troubling parallel emerges—the “cold-steel problem.” AI, increasingly trained on its own synthetic outputs, risks a self-referential spiral, eroding the authenticity and diversity of information. Like steel laced with radiation, AI-generated data threatens to corrode the tools of knowledge, leaving us with a homogenized, unreliable digital landscape.
The pre-AI era offered a rich tapestry of human thought—letters, books, forums, and early websites brimmed with unfiltered perspectives. These were the “cold steel” of data: imperfect, often chaotic, but rooted in reality. Today, AI’s insatiable appetite for content—web-scraped, algorithmically churned—has shifted the balance. A 2024 Nature study warns of “model collapse,” where AI trained on synthetic data loses the nuanced “tails” of human experience, converging toward bland, repetitive outputs. Wikipedia, once a bastion of human collaboration, now grapples with AI-generated articles—5% of new English entries in 2024 bore hallmarks of automation, often shallow and poorly sourced. This isn’t mere noise; it’s a distortion, amplifying errors and biases with each recursive loop, like a photocopy of a photocopy fading into illegibility.
The mechanics of this spiral are insidious. AI models, fed on web data increasingly tainted by their own outputs, risk “Model Autophagy Disorder” (MAD)—a vivid term for systems consuming themselves. A 2017 self-driving car crash, caused by mislabeled data failing to distinguish a truck from a bright sky, illustrates the stakes: errors compound, reality distorts. Posts on X lament search engines returning AI-crafted drivel—slick but soulless—while human voices struggle to break through. The counterargument, that synthetic data fills gaps in niche domains like coding, holds limited weight. Even in verifiable fields, the loss of diverse, human-generated inputs risks outputs that are technically correct but creatively barren, a digital equivalent of bollocks masquerading as insight.
The implications are stark: an information ecosystem choked by self-referential sludge threatens not just AI’s utility but society’s capacity for truth-seeking. If unchecked, this spiral could render knowledge a hollow echo chamber, antithetical to the vibrant complexity of human thought. Mitigation demands urgency—prioritizing human-curated datasets, enforcing transparency in data provenance, and developing tools to filter AI’s footprint. Blockchain-based data authentication or crowd-sourced verification could anchor AI in reality, preserving the “cold steel” of human insight. Yet, these solutions require collective will, a resistance to the seductive ease of automation’s churn. Without action, the fallout risks a digital dark age where truth drowns in synthetic noise.
The cold-steel problem is no mere technical glitch; it’s a philosophical reckoning. AI, for all its prowess, cannot replicate the spark of human creativity or the grit of lived experience. As we stand at this precipice, the choice is clear: safeguard the authenticity of human data or surrender to a future where information is a pale shadow of its potential. The shipwrecks of our pre-AI past hold treasures worth salvaging—not just for AI’s sake, but for the soul of our shared knowledge. Act now, or the corrosion of our digital ecosystem will be a legacy of our own making.

Sources
- Shumailov, I., et al. (2024). AI models collapse when trained on recursively generated data. Nature, 631, 755–759. https://www.nature.com/articles/s41586-024-07566-y[](https://www.nature.com/articles/s41586-024-07566-y)
- Alemohammad, S., et al. (2024). Self-Consuming Generative Models Go MAD. International Conference on Learning Representations (ICLR). https://news.rice.edu/news/2024/breaking-mad-generative-ai-could-break-internet[](https://www.sciencedaily.com/releases/2024/07/240730134759.htm)
- Model collapse. (2024, March 6). Wikipedia. https://en.wikipedia.org/wiki/Model_collapse[](https://en.wikipedia.org/wiki/Model_collapse)
- Rice University. (2024, July 30). Breaking MAD: Generative AI could break the internet, researchers find. ScienceDaily. https://www.sciencedaily.com/releases/2024/07/240730134750.htm[](https://www.sciencedaily.com/releases/2024/07/240730134759.htm)
- Kempe, J., et al. (2024). A Tale of Tails: Model Collapse as a Change of Scaling Laws. International Conference on Machine Learning (ICML). https://nyudatascience.medium.com/overcoming-the-ai-data-crisis-a-new-solution-to-model-collapse-2d36099be53c[](https://nyudatascience.medium.com/overcoming-the-ai-data-crisis-a-new-solution-to-model-collapse-ddc5b382e182)
- Shumailov, I., et al. (2023). AI-Generated Data Can Poison Future AI Models. Scientific American. https://www.scientificamerican.com/article/ai-generated-data-can-poison-future-ai-models/[](https://www.scientificamerican.com/article/ai-generated-data-can-poison-future-ai-models/)
The Bloodroot is a small vegan restaurant. Their crime? Having the absolute gall and audacity to state – in a feminist space no less – that they believe in supporting women born women. It is enough of a transgression to bring the trans-hoarde along with the usual threats, cyberbullying, and harassment (typical aggressive male behaviour) that uppity women (in this case two elderly lesbians) get for not bowing down to prescribed male reality.
“Bloodroot Vegetarian Restaurant has been a beloved staple of Bridgeport, Conn. for more than 40 years, serving up feminist-influenced plant-based fare to the likes of Audre Lordre and Adrienne Rich, as well as dedicated locals. But a recent review alleging that owners Selma Miriam and Noel Furie reject transgender customers has set off a firestorm online.
For many, the fallout has echoes of the Michfest debate, which divided LGBTQ women for more than two decades. And while the review has since been removed, it appears in screenshots on Facebook, and Bloodroot’s own statement in response has kept the conversation going.
In the review from late December, a customer writes that upon a visit to Bloodroot, she was having lunch with a friend when she began speaking with Miriam and Furie about up Lorde having been a friend of the restaurant. The conversation turned to the customer’s own dream of having a “queer and trans intentional community and sanctuary.”
“Immediately Selma and Noel looked at one another and Selma said, ‘[W]e strongly believe in supporting only women born women here,” the customer alleges. “‘[W]e are disgusted by men who think they can put on dresses and nail polish and pump themselves up with nail polish and pump themselves with chemicals and say they are women. [T]hey just aren’t. and we will never support them.'”
The customer then she she felt uncomfortable and afraid, and is now advocating that others “refuse to support them and encourage others to do the same.”
Both Miriam and Furie declined to be interviewed for this piece, but in a Dec. 31 statement posted to their Facebook page, Bloodroot says the controversy stemmed from a conversation with a new customer who asked if they knew of an establishment that catered to trans people.
“We didn’t,” the statement reads, “but since we are not trans, it wasn’t all that interesting to us personally and stated that for us, we prefer women only spaces. This comes from our history. When Bloodroot first started in the 70’s [sic] we were trying to create a space specifically safe for women, since there were so few places like that at the time. Of course even back then we were open and welcoming to everyone, not just women.”
The post goes on to say that customer misunderstood that reply and wrote a post online slamming Bloodroot.
“We understand this is a subject matter that many people are passionate about, but we feel this anger is misguided and misplaced,” Bloodroot says in the statement. “Regardless of how you feel about Bloodroot’s stand on this, we will continue to be a welcoming space for all types of people, including those that are transgender, and treat everyone with respect.”
After the Restaurant’s FB post, Charlie Rae answers the call and deftly puts the situation into perspective (especially the last paragraph).

Don’t let someone who “leet speaks” onto your computer. Ever.
I’m such a non-fan of passwords. Keeping track of all that shite is tedious. So here I am doing my best when along comes the CBC to make life even more difficult.
“If your password is on the list below you had better change it.
Among the 25 most common passwords among 3.3 million that were leaked online last year, the top two were once again “123456” and “password,” according to a company that provides password management software.”
Based on its analysis, SplashData recommends that when crafting your password:
- Don’t use keyboard patterns e.g. “qwertyuiop” from the top row of letters
- Don’t use a favourite sport – baseball and football were both in the Top 10, with hockey, soccer and golf in the Top 100.
- Don’t use your birthday or birth year. People in their early 20s seemed to be especially guilty of this, with the years 1989 to 1992 all in the top 100.
- Don’t use common names – michael, jennifer, thomas, jordan, hunter, michelle, charlie, andrew and daniel were all in the Top 50.
Here’s the entire list:
-
123456
-
password
-
12345
-
12345678
-
qwerty
-
1234567890
-
1234
-
baseball
-
dragon
-
football
-
1234567
-
monkey
-
letmein
-
abc123
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111111
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mustang
-
access
-
shadow
-
master
-
michael
-
superman
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696969
-
123123
-
batman
-
trustno1
So there you go, now out and make yourself and your accounts more secure and less accessible to yourself. You are welcome.
Let it be said up front that this cranky second waver bears no animus with regards to hamsters, electric vehicles, or dancing. Yet, once these elements are mixed into the toxic soup of everyone’s favourite capitalistic patriarchal construct – better known as ‘our society’ – hilarity is bound to ensue.
The advertisement in whole, before we begin.
This commercial is about selling cars. (Duh!) But who is the target audience? (if you thought hamsters, please leave now there are places better suited for your attentions). Let’s break this down and take a look at the characters.
Science Hamster #1 – Red bow-tie, suspenders.

Science Hamster#2 – Red bow-tie, red glasses and polka dot shirt.

Science Hamster#3 – Rasta hat, white shirt.

Because not all dudes are not into science! Bonus marks for catching the racial commentary this characterization is making.
Female Hamster in Ball – Brown and cute. Context wise we don’t know the ball hamster is female, but with time spent on establishing a connection one could assume.

Small, helpless, and cute. Thematic material anyone?
We’re 10 seconds into the commercial and what do we have here – 3 male represented characters creating, designing, and actively teching out with all sorts of futuristic displays and machinery. The female role, to smiled and waved at; the unsurprising passive receptacle for male attentions.
Audio note – “Baby I’m preying on you tonight. Hunt you down eat you alive,. Just like animals (x2). Ah yes because the predator/prey relationship is so sexy, and filled with equality too!
Well nothing new here under the sun so far, but as with most patriarchal adventures it gets worse the farther you go. Our intrepid female hamster gets herself into a jam by wheeling her ball into the experimental area and is zapped along with the vehicle by the transmogrifying beams of science.

Oh, silly female! Caution be thrown to the wind cause she doesn’t get Science!
Our first glimpse of her portents much of what is to come. Disembodied woman parts with feminine signifiers for the winz!

The body parts of women – sexy!
The requisite Male gaze.

To quote Keanu Reeves: Whoa…
And after a full body pan, we as viewers to get to experience the male gaze. Just some reinforcement in case you missed the objectification the first time around.

Audience gets to objectify her to, as women should be judged by the quality of their tuckus.
Now that we have primed the audience for sexual objectification, lets use it to sell the damn car!

Inviting female = inviting car?
Where is the female empowerment (do tell my Third Wave friends)?!? Oh wait the power of love. How charmingly original for a female character (do contrast this with the creator, the scientist, the engineer).

Empowerful stuff going on here.
Oh, dudes like their technology more than any single vampy female. Let’s get a shot of her looking flummoxed so we can reiterate the “female body selling car” angle again. We do remember the advertising truism – the sexual objectification of women sells.

Damn, they picked me over a car, what could they possibly after?
Our intrepid dudes roll to the nearest pet store to ‘pick up some chicks’. Consider the perceived power differential – the dudes looming over a cage of helpless females – and of course the anvilicious buying of women for happy fun sexy times.

Write your own snark about how empowering prostitution is…
So cue more science and boom! Let the female empowerment roar while striking sexy poses for dudes (science and/or otherwise)!

Huh, because vamping for dudes is approved female behaviour!
Recently bough females remarkable receptive to their buyers, with nuzzling and other overt signs of female powah affection.

Oh, we like you dudes and our role as eye-sex-candy and everything is awesome, see how much fun are having?
Cue the formation dancing with of course, our protagonists front and centre, we must never forget the centrality of the man and his power.

Never forget who is the subject and who is the object.
And thus endeth the analysis.
Going through this post made me think of all the conversations, mostly with men, about how we don’t need feminism anymore because we are an equal society now thus there is no use for feminism or feminist analysis. This was a cute commercial until you actually look at the underlying patriarchal messages that surprisingly happen to dovetail nicely how society perceives, and thus, how society treats women in 2014.
You could knock me over with a feather given how surprised I am about the level of misogyny present in our media.
As always, IBTP.







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