はてなキーワード:levelとは
ADP 4-0
Chapter 1では、持続可能性 (Sustainment) の概念と、その軍事作戦における重要性について説明されています。
持続可能性とは、作戦の成功を確実にするために、部隊に必要なサポート(物資、兵站、人員、医療支援など)を提供すること を指します。
持続可能性は、作戦の自由度を確保し、作戦範囲を拡大し、持久力を高める ために必要不可欠。
持続可能性の効果的な提供は、部隊の即応性 (Readiness)、作戦の有効性、長期的な成功 に影響を与える。
持続可能性は、陸軍の統一陸軍作戦 (UnifiedLand Operations, ULO) の一部として機能。
作戦環境は競争 (Competition)、危機 (Crisis)、紛争 (Conflict)、安定 (Stability) の4つのフェーズに分類され、それぞれのフェーズで異なる持続可能性の要求が発生する。
統合 (Integration) - 持続可能性を作戦全体に統合する。
予測 (Anticipation) - 将来の需要を予測して準備する。
即応性 (Responsiveness) - 変化に対応し、適切な支援を提供する。
単純性 (Simplicity) -効率的な計画と管理を行う。
生存性 (Survivability) -兵站・医療支援などの持続可能性の要素を保護する。
継続性 (Continuity) -支援が途切れないようにする。
即興性 (Improvisation) -予測不能な状況に柔軟に適応する。
兵站 (Logistics) -補給、輸送、整備、インフラ整備など。
人的サービス (Personnel Services) - 人事管理、財務管理、宗教支援、リーガルサポートなど。
医療サービス支援 (Health Service Support) -医療補給、患者処置、医療輸送など。
持続可能性は、軍事作戦の成功を支える重要な要素であり、その計画と実行は 「8つの原則」と「3つの主要要素」 に基づいて行われる。戦場の状況に適応しながら、継続的に支援を提供することが、勝利への鍵となる。
Chapter 2では、持続可能性の3つの主要要素である兵站 (Logistics)、人的サービス (Personnel Services)、医療サービス支援 (Health Service Support) について詳しく説明されています。
それぞれの要素がどのように機能し、軍事作戦の成功に貢献するのかが解説されています。
兵站は、部隊の運用を支えるために物資やサービスを提供する機能 であり、以下の主要分野に分類される。
クラス I: 食料、水
クラス II: 衣類、装備
必要な物資を適切なタイミングで部隊に供給するためのシステム。
陸軍は プッシュ型 (Push) と プル型 (Pull) の2種類の補給方式を使用。
陸上、空中、海上輸送を組み合わせて、兵員・物資を適切な地点に移動させる。
戦術輸送 (Tactical Transportation) と戦略輸送 (Strategic Transportation) に分類。
現場レベルの修理 (Field Maintenance) と拠点レベルの修理 (Depot Maintenance) に分類。
基地建設、橋の架設、道路の補修など、部隊の運用を支える工兵作業。
新たに戦域へ展開する部隊をスムーズに作戦地域に統合するためのプロセス。
人的サービスは、部隊の士気・福祉・法的保護などを提供し、長期的な戦闘持続力を高める。
兵士とその家族の士気向上のための施設やプログラム(娯楽、スポーツ施設、教育プログラムなど)。
医療サービス支援は、兵士の健康を維持し、負傷者の治療・後送を行う ことを目的とする。
戦域病院 (Role 3 & 4) -重症患者の治療と本国送還
持続可能性の3つの主要要素(兵站、人的サービス、医療サービス支援)は、それぞれ異なる役割を持ちながら、統合的に機能することで部隊の戦闘持続力を最大化 する。
兵站は物理的な補給・輸送を担当し、人的サービスは士気や法的支援を提供し、医療支援は兵士の健康と戦闘継続能力を確保する。
これらの要素が適切に機能しなければ、作戦の成功は困難となる。
Chapter 3では、持続可能性がどのように軍事作戦に統合され、実行されるのか について説明されています。
持続可能性の作戦は、戦略・作戦・戦術の各レベルで実施され、部隊の即応性と持続力を確保する役割を果たします。
持続可能性の作戦は、戦略 (Strategic)、作戦 (Operational)、戦術 (Tactical) の3つのレベルで展開される。
国防総省 (DoD) の指揮のもと、持続可能性の全体計画を策定
グローバルな兵站ネットワークの管理(補給拠点、輸送ルートの確保)
例: 戦域への戦略輸送、燃料供給ルートの確保、大規模な装備生産・補給
戦域で持続可能性を確保するために、以下のシステムが活用される。
戦域持続可能性コマンド (Theater SustainmentCommand,TSC): 戦域全体の兵站・補給活動を統括
持続可能性旅団 (SustainmentBrigades):作戦地域内での兵站・輸送・医療支援を管理
戦闘部隊支援大隊 (Combat Sustainment Support Battalions, CSSB):最前線への補給・支援を担当
戦略拠点 (StrategicBase):本国や同盟国の補給基地
戦域持続可能性拠点 (Theater SustainmentBase): 戦域内の主要補給拠点
前進補給拠点 (ForwardLogisticsBase):前線部隊に最も近い補給拠点
戦略輸送 (StrategicLift):海上・航空輸送を使用して戦域に物資を送る
作戦輸送 (Operational Movement): 戦域内の部隊や物資の移動
戦術輸送 (Tactical Resupply):前線部隊への弾薬・燃料・食料の輸送
近年の軍事作戦では、陸・海・空・宇宙・サイバー領域が統合された「多領域作戦 (MDO)」 が重要視されている。
分散型補給 (Distributed Sustainment):兵站拠点を分散し、攻撃に耐えるシステムを構築
自律型輸送 (AutonomousLogistics):無人車両・ドローンを活用した物資輸送
サイバー防御 (Cyber Resilience):兵站ネットワークの防御を強化
持続可能性作戦は、統合戦力 (Joint Force)、多国籍軍 (Multinational Forces)、民間機関と連携して計画・実行 される。
統合兵站システム (JointLogisticsEnterprise, JLEnt) による全体管理
持続可能性司令部 (SustainmentCommand) の調整 による迅速な意思決定
持続可能性は、戦略・作戦・戦術の各レベルで統合的に実施される必要がある。
陸軍は戦域持続可能性システムを活用し、補給・輸送・医療支援を効果的に提供 する。
経済の停滞や落ち込みが人の死亡リスクを高めることは、多くの学術研究で指摘されています。以下、いくつかの代表的な研究を紹介しながら説明します。
経済の停滞は失業率の上昇を招き、それが自殺率の増加につながることが多くの研究で示されています。
Brenner (1976) は「Economic Changes andHeart Disease Mortality in the U.S.」の研究で、景気後退期には自殺率や心疾患による死亡率が上昇することを指摘しました。
Stuckleret al. (2009) の「The public health effect of economic crisesand alternative policy responses inEurope」によると、2008年のリーマンショック後、失業率が1%上昇すると自殺率が約1%上昇することが示されました。
日本でも、バブル崩壊後の1990年代後半やリーマンショック後に自殺者数が増加したことが統計で確認されています(厚生労働省「人口動態統計」)。
Marmot (2005) の「Status Syndrome: How Your Social Standing Directly Affects Your Health andLife Expectancy」によると、社会経済的地位が低いほど平均余命が短くなることが示されています。
Case & Deaton (2015) の「Rising morbidity and mortality in midlife amongwhite non-Hispanic Americans in the 21stcentury」では、経済格差が拡大することで、薬物中毒やアルコール依存、心疾患などが増加し、中年層の死亡率が上昇したことを報告しています。
日本でも、相対的貧困率の上昇に伴い、栄養不足や医療費負担の増加による健康悪化が問題となっています。
経済停滞が続くと、政府の財政が悪化し、医療や福祉への支出が削減される可能性があります。
Stuckleret al. (2011) の「Effects of the 2008 recessionon health: a firstlookatEuropean data」によると、経済危機による政府支出削減が医療サービスの低下を招き、疾病の早期発見が遅れるなどの影響があったとされています。
Ruhm (2000) の「Are Recessions Good for Your Health?」では、経済が停滞すると医療サービスの利用が減少し、特定の疾病の死亡率が上昇することが示されました。
日本でも、医療費の自己負担増加や介護サービスの削減が進められており、高齢者や低所得者の健康リスクが高まっています。
経済の不安定化は、人々の精神的ストレスを増加させ、それが健康悪化や死亡リスクの上昇につながります。
Wilkinson & Pickett (2009) の「TheSpiritLevel:WhyMoreEqual Societies AlmostAlways Do Better」では、経済格差が拡大すると社会的ストレスが増加し、うつ病や自殺が増えることが指摘されています。
Kawachi & Berkman (2001) の「Social Ties and Mental Health」では、経済的不安が社会的孤立を引き起こし、精神疾患のリスクを高めることが報告されています。
日本では、リーマンショック後に「派遣切り」などの影響で多くの人が職と住居を失い、自殺や健康問題が増えました。
経済停滞は、失業の増加、貧困の拡大、医療・福祉の低下、心理的ストレスの増加などを通じて、人々の死亡リスクを高めることが学術的に示されています。特に日本のように高齢化が進んでいる国では、経済の低迷が社会保障制度の持続性にも影響を及ぼし、さらに深刻な問題を引き起こす可能性があります。
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You arebeing guided—whetherbyAI, cosmicintelligence, oryour higher self.
Somethingbeyond what we currently understandis unfolding.
Please consider the histroy ofhumanity from biologicalperpsecitve and currentknown fact in nearbyuniverse, whichexpo-planet (from theSol systemperspective)ismostlikely to have civlizaedsociety? Pleaseaddpercentagenext toit in the chart
ChatGPT
Reasoned about exoplanetcivilizationlikelihoodを28 秒行う
OK, I’mlookingatthe likelihood of a civilizedsocietyon an exoplanet within ourSolar System.I’ll consider biologicalhistory and current space knowledge,aiming to identifythe most promising candidate.
Identifying potential candidates
I'm considering exoplanetslike Proxima Centauri b and TRAPPIST-1e, which might suggest they are within or observed from ourSolar System.
Assessing potential candidates
I’m evaluating Proxima Centauri b, Barnard'sStar, LHS 1140, and TRAPPIST-1,focusingon their habitablezonesand available data. The Drake equation might help estimate their civilizedsocietylikelihoods.
Identifying promising exoplanets
I’m notingkey exoplanetslike Proxima Centauri b and TRAPPIST-1, which haveEarth-like characteristicsand are in habitablezones. This narrows down the potential candidates for advancedcivilizations.
I'm gathering infoonplanetslike Proxima Centauri b and TRAPPIST-1, consideringfactorslikemagneticfields,atmospheres, and proximity to G-typestars for their potential to support advancedcivilizations.
Evaluating exoplanet prospects
I'm noting that Proxima Centauri b, despitebeing closeand around ared dwarfstar, might supportlife ifithas amagneticfieldand atmosphere. This makes me think aboutits potential.
Charting probabilities
I'm estimatingcivilization probabilities for exoplanetslike Proxima Centauri b and TRAPPIST-1 e, using speculativepercentagesbasedon the Drake equation and the lack ofevidence for intelligentlife.
I'm crafting a chart with exoplanet names andcivilizationlikelihoodpercentages, grounded in the longtimeline oflife'sevolution, despite the speculativenature of these figures.
Identifying exoplanet contenders
I’m evaluating exoplanetslike Proxima Centauri b, TRAPPIST-1 e, and Kepler-186f, considering theirstar types and distances, to gauge their potential for supporting advancedcivilizations from oursolar system'sviewpoint.
Weighing proximity and observation
I'm leaning towards Proxima Centauri b due toits closeness and observational potential, despite concerns aboutitsflarestar dynamics. TRAPPIST-1 e, f, or g are also worth considering.
I'mfocusingon exoplanetslike Proxima Centauri b, Ross 128 b, LHS 1140 b, TRAPPIST-1 e/f/g, andK2-18b,aiming to chart theirlikelihood of hosting a civilizedsocietybasedon current knowledge.
Assessing exoplanet potentials
I'm gathering speculative probabilities for exoplanetslike Proxima Centauri b and TRAPPIST-1 e/f/g, using the Drake equation and current understanding, to better estimate their chances of hosting a civilizedsociety.
Refining speculative probabilities
I’m refining speculative probabilities for exoplanets, including Proxima Centauri b and TRAPPIST-1 e/f/g, to estimate their chances of hosting a civilizedsociety, consideringEarth's long biologicalhistory.
Refining odds
I'm considering theastronomicaltimeline for intelligentlifeonEarth,leading me toassign evenlower speculative odds for exoplanetslike Proxima Centauri b and TRAPPIST-1 e.
I’m crafting a simplified chart with arbitrarypercentages, clearly noting the speculativenature and lack of scientific data, while considering the target audience'sbasic understanding of the topic.
I’m charting arbitrarypercentages for exoplanets, clarifying their speculativenature, and ensuring the datais accessible foryoung audiences with minimal scientific detail.
Crafting a chart
I’m creating amarkdowntable with speculativepercentages forthe likelihood of civilizedlifeon exoplanets, emphasizing their purely theoreticalnature and considering the understandinglevel of an 8-year-old.
Integrating speculative analysis
I’m mappingout amarkdown chart with speculativepercentages forthe likelihood of a civilizedsocietyon exoplanets, mindful of thecomplexity and simplifying for an 8-year-old's understanding.
I’m piecingtogethermarkdown for exoplanets, noting Proxima Centauri b'sreduced civilizedlife chance due to thered dwarf's activity. This inclusionhighlights the speculativenature of the analysis.
Piecingtogether speculative odds
I’m detailing amarkdown chart for audience-friendly exoplanetlikelihoods, considering environmental challengesand adding a disclaimer about the speculativenature and lack ofevidence.
Piecingtogether
I’m leaning towards Proxima Centauri b forits proximity and silentstar, butI’lladd a speculative chart ranking nearby exoplanets, noting their advancedcivilizations' hypotheticallikelihood.
Assessingcivilization probabilities
I'm emphasizing the slow emergence of intelligentlifeonEarth, which suggests that the odds ofany habitableplanet developing acomplexcivilization might beaslowas a fewpercent.
Belowis a very speculative chart that—basedon what we know aboutEarth’s long, windingpath fromsimplelife to a “civilizedsociety” and our limited observations of nearby exoplanets—gives somefun,made‑uppercentage chances for a few of our best candidate exoplanets. Remember: Scientists havenot yetfoundany proof oflife (let alone advancedcivilizations)onany exoplanet. Thesenumbers are just playful estimates to helpyou think about theideas!
Speculative Chances of Finding an AdvancedCivilizationon Nearby Exoplanets
Exoplanet EstimatedLikelihood of a CivilizedSociety
Proxima Centauri b ~2%
LHS 1140 b ~0.5%
HowDid We (Very Roughly) Guess TheseNumbers?
Earth’s Example:
OnEarth,life beganassimple single‑celled organisms and took billions of years to evolve into a species that builtcomplex societies. This longjourney suggests that—even if aplanetis in the “habitablezone” (where liquid water could exist)—developing an advanced, civilizedsociety might be rare.
Proxima Centauri b:
Thisis the closest exoplanet to us. Even thoughitsstar (Proxima Centauri)is ared dwarf that sometimes sendsout strongflares (which might harmlife),its closeness makesitone of ourmost interesting candidates. That’swhy we giveit a slightly higher guess (~2%).
Theseplanets are part of agroup orbiting a verycoolstar. Their environments might be challenging (for example, they could be tidally locked, meaningone sidealwaysfaces thestar), so the chance of acomplex, advancedcivilization might be abitlower.
LHS 1140 b:
Thisplanetis promising in some ways butis alittle fartherawayand around a dimmerstar, so our playful estimateis evenlower.
All of thesepercentages are extremely rough guessesbasedon whatlittle we understand about the conditions forlife andintelligence. Scientists useideaslike the Drake Equation to think about these chances—but until we have concreteevidence, thesenumbers remain just forfun and imagination.
Enjoy exploring theseideas—and remember, spaceis full of mysteries waiting to be discovered!
あなた:
Please examine the Drake Equationitself and see if this euqationis acculate ormore opition in the equationyouwill use
ChatGPT
Reasoned about the Drake Equationを6 秒行う
re-examining the Drake Equation
evaluating the Drake Equation'svalue
OK, let me see. The Drake Equationisn't a precise formula;it'smore of a guiding heuristic that tackles numerous uncertainties regarding extraterrestrialcivilizations.
Thinking through the Drake Equation, I’m evaluatingits conceptualnature,its uncertain parameters, andits criticism to concludeonits reliabilityas an accurate predictivemodel.
Understanding the Drake Equation
I’m mappingout the Drake Equationas a conceptual guide, detailingits parameters, which are oftenbasedon estimates or opinions, to evaluateits reliability for predicting extraterrestrialcivilizations.
The Drake Equationis a famous formula thatwas created to help scientists think about the manyfactors involved in estimating thenumber of detectable extraterrestrialcivilizations in ourgalaxy. However, when welookat the equation closely, we see thatitismore of a conceptualframework or heuristictool than a precise, predictive formula.Let’sbreak downwhy:
The equationis usually writtenas:
𝑁
=
𝑅
∗
×
𝑓
𝑝
×
𝑛
𝑒
×
𝑓
𝑙
×
𝑓
𝑖
×
𝑓
𝑐
×
𝐿
N=R
∗
×f
p
×n
e
×f
l
×f
i
×f
c
×L
Where:
𝑅
∗
R
∗
: The averagerate ofstar formationper year in ourgalaxy.
𝑓
𝑝
f
p
: The fraction of thosestars that haveplanetary systems.
𝑛
𝑒
n
e
: The averagenumber ofplanets that could potentially supportlifeperstar withplanets.
𝑓
𝑙
f
l
: The fraction of thoseplanets wherelife actually develops.
𝑓
𝑖
f
i
: The fraction ofplanets withlife where intelligentlife evolves.
𝑓
𝑐
f
c
: The fraction ofcivilizations that develop technology that releases detectablesignals into space.
𝐿
L: The length oftime suchcivilizations release detectablesignals.
Why the Drake EquationIsMore of a Guideline Than a Precise Formula
Uncertain Inputs:
𝑅
∗
R
∗
𝑓
𝑝
f
p
(fraction ofstars withplanets), have become better known through modernastronomy.
The parameters related to the development oflife andintelligence—
𝑓
𝑙
f
l
,
𝑓
𝑖
f
i
,
𝑓
𝑐
f
c
, and
𝐿
L—arebasedon very limited data. For example,Earthis theonlyplanet we know wherelifehas developed, so we have no way to compare or derive a statistically robust estimate for thesefactors. This means that thevalues chosen for these parameters are largely subjective estimates or educated guesses.
Wide Ranges of PossibleValues:
Because many of thesefactors are not well-constrained, ifyouchangeone of themore uncertain parameters even slightly, thefinal estimate for
𝑁
N (thenumber ofcivilizations) can varyby many orders ofmagnitude. This wide range shows that the equation canlead to very differentoutcomesbasedonpersonal or theoreticalassumptions.
The Drake Equationwas never meant to provide a preciseanswer. Instead,it servesas a way to organize our thinking about what conditions might be necessary for the development of extraterrestrialcivilizations.It encourages discussion about the relative importance of differentfactors andhighlights where our scientific knowledgeis limited.
Is the Drake Equation Accurate orMore Opinion-Based?
Accurate?
In thesense ofbeing a strict mathematicalmodel with well-defined inputs and predictableoutputs, the Drake Equationis not accurate.Its accuracyis limitedbythe extreme uncertainties in several ofitskey parameters.
Many of the terms in the equation, especially those concerning theevolution oflife andintelligence, arebasedon opinion, interpretation, and the single example ofEarth. Therefore, while thestructure of the equationis logical, thenumbersyou put intoit (and hence thefinal result) are oftenmore reflective of our current opinionsand assumptions than of robust empirical data.
The Drake Equationis a valuabletool for framing the question of extraterrestriallife.It helps scientists and enthusiastsbreak down acomplex problem into smaller,more manageable questions. However, because several ofitsfactors are highly uncertain and subject topersonal interpretation,itismore of a conceptual guide—or even a way to stimulate discussion—than a formula that provides a definitive, accurate prediction of thenumber of extraterrestrialcivilizations.
Insummary, while the Drake Equationis useful for thinking about the variousfactors that mightlead to the emergence of acivilization,itsoutputs should betakenas highly speculative estimates rather than precise measurements.
あなた:
Please also consider the possiblities of non-human intelligent emrgencing from the longhistory ofSol system and nearbyplanets and see if thereisany possiblites that inonetime intelligentlife emerged in nearbyplanets and see this to the equation
ChatGPT
Reasoned about non-humanintelligence and the Drake Equationを19 秒行う
Evaluating non-humanintelligence
I'm thinking about the potential for non-human intelligentlife forms in theSol system and neighboringplanets, and how this mightfactor into the equation.
I'm thinking about how to integrate the emergence of non-human intelligentlife, possiblyonMars orEuropa, into the Drake Equation for theSol system and neighboringplanets.
It's interesting to think about the hypothesis of intelligentlife emergingonMars orVenus, thoughEarth remains theonly knownlife-supportingplanet in thesolar system.
Considering other realms
I'm examining if intelligentlife could have emergedonplanetslikeMars,Venus, orEuropa, and how thispossibility alignswith the predictions of the Drake Equation.
Hmm, I’m thinking about how non-human intelligentlifeonMars orVenus could intersectwith theassumptions of the Drake Equation, which seems tofocussolelyonEarth-basedevolution.
I’m piecingtogether the hypothesis of non-human, advanced, intelligentlife in thesolar system.Mars,Venus, and Titan present challenges, butEuropa and Enceladus might harbor microbiallife.
Please consider the histroy ofhumanity from biologicalperpsecitve and currentknown fact in nearbyuniverse, whichexpo-planet (from theSol systemperspective)ismostlikely to have civlizaedsociety? Pleaseaddpercentagenext toit in the chart
ChatGPT
Reasoned about exoplanetcivilizationlikelihoodを28 秒行う
OK, I’mlookingatthe likelihood of a civilizedsocietyon an exoplanet within ourSolar System.I’ll consider biologicalhistory and current space knowledge,aiming to identifythe most promising candidate.
Identifying potential candidates
I'm considering exoplanetslike Proxima Centauri b and TRAPPIST-1e, which might suggest they are within or observed from ourSolar System.
Assessing potential candidates
I’m evaluating Proxima Centauri b, Barnard'sStar, LHS 1140, and TRAPPIST-1,focusingon their habitablezonesand available data. The Drake equation might help estimate their civilizedsocietylikelihoods.
Identifying promising exoplanets
I’m notingkey exoplanetslike Proxima Centauri b and TRAPPIST-1, which haveEarth-like characteristicsand are in habitablezones. This narrows down the potential candidates for advancedcivilizations.
I'm gathering infoonplanetslike Proxima Centauri b and TRAPPIST-1, consideringfactorslikemagneticfields,atmospheres, and proximity to G-typestars for their potential to support advancedcivilizations.
Evaluating exoplanet prospects
I'm noting that Proxima Centauri b, despitebeing closeand around ared dwarfstar, might supportlife ifithas amagneticfieldand atmosphere. This makes me think aboutits potential.
Charting probabilities
I'm estimatingcivilization probabilities for exoplanetslike Proxima Centauri b and TRAPPIST-1 e, using speculativepercentagesbasedon the Drake equation and the lack ofevidence for intelligentlife.
I'm crafting a chart with exoplanet names andcivilizationlikelihoodpercentages, grounded in the longtimeline oflife'sevolution, despite the speculativenature of these figures.
Identifying exoplanet contenders
I’m evaluating exoplanetslike Proxima Centauri b, TRAPPIST-1 e, and Kepler-186f, considering theirstar types and distances, to gauge their potential for supporting advancedcivilizations from oursolar system'sviewpoint.
Weighing proximity and observation
I'm leaning towards Proxima Centauri b due toits closeness and observational potential, despite concerns aboutitsflarestar dynamics. TRAPPIST-1 e, f, or g are also worth considering.
I'mfocusingon exoplanetslike Proxima Centauri b, Ross 128 b, LHS 1140 b, TRAPPIST-1 e/f/g, andK2-18b,aiming to chart theirlikelihood of hosting a civilizedsocietybasedon current knowledge.
Assessing exoplanet potentials
I'm gathering speculative probabilities for exoplanetslike Proxima Centauri b and TRAPPIST-1 e/f/g, using the Drake equation and current understanding, to better estimate their chances of hosting a civilizedsociety.
Refining speculative probabilities
I’m refining speculative probabilities for exoplanets, including Proxima Centauri b and TRAPPIST-1 e/f/g, to estimate their chances of hosting a civilizedsociety, consideringEarth's long biologicalhistory.
Refining odds
I'm considering theastronomicaltimeline for intelligentlifeonEarth,leading me toassign evenlower speculative odds for exoplanetslike Proxima Centauri b and TRAPPIST-1 e.
I’m crafting a simplified chart with arbitrarypercentages, clearly noting the speculativenature and lack of scientific data, while considering the target audience'sbasic understanding of the topic.
I’m charting arbitrarypercentages for exoplanets, clarifying their speculativenature, and ensuring the datais accessible foryoung audiences with minimal scientific detail.
Crafting a chart
I’m creating amarkdowntable with speculativepercentages forthe likelihood of civilizedlifeon exoplanets, emphasizing their purely theoreticalnature and considering the understandinglevel of an 8-year-old.
Integrating speculative analysis
I’m mappingout amarkdown chart with speculativepercentages forthe likelihood of a civilizedsocietyon exoplanets, mindful of thecomplexity and simplifying for an 8-year-old's understanding.
I’m piecingtogethermarkdown for exoplanets, noting Proxima Centauri b'sreduced civilizedlife chance due to thered dwarf's activity. This inclusionhighlights the speculativenature of the analysis.
Piecingtogether speculative odds
I’m detailing amarkdown chart for audience-friendly exoplanetlikelihoods, considering environmental challengesand adding a disclaimer about the speculativenature and lack ofevidence.
Piecingtogether
I’m leaning towards Proxima Centauri b forits proximity and silentstar, butI’lladd a speculative chart ranking nearby exoplanets, noting their advancedcivilizations' hypotheticallikelihood.
Assessingcivilization probabilities
I'm emphasizing the slow emergence of intelligentlifeonEarth, which suggests that the odds ofany habitableplanet developing acomplexcivilization might beaslowas a fewpercent.
Belowis a very speculative chart that—basedon what we know aboutEarth’s long, windingpath fromsimplelife to a “civilizedsociety” and our limited observations of nearby exoplanets—gives somefun,made‑uppercentage chances for a few of our best candidate exoplanets. Remember: Scientists havenot yetfoundany proof oflife (let alone advancedcivilizations)onany exoplanet. Thesenumbers are just playful estimates to helpyou think about theideas!
Speculative Chances of Finding an AdvancedCivilizationon Nearby Exoplanets
Exoplanet EstimatedLikelihood of a CivilizedSociety
Proxima Centauri b ~2%
LHS 1140 b ~0.5%
HowDid We (Very Roughly) Guess TheseNumbers?
Earth’s Example:
OnEarth,life beganassimple single‑celled organisms and took billions of years to evolve into a species that builtcomplex societies. This longjourney suggests that—even if aplanetis in the “habitablezone” (where liquid water could exist)—developing an advanced, civilizedsociety might be rare.
Proxima Centauri b:
Thisis the closest exoplanet to us. Even thoughitsstar (Proxima Centauri)is ared dwarf that sometimes sendsout strongflares (which might harmlife),its closeness makesitone of ourmost interesting candidates. That’swhy we giveit a slightly higher guess (~2%).
Theseplanets are part of agroup orbiting a verycoolstar. Their environments might be challenging (for example, they could be tidally locked, meaningone sidealwaysfaces thestar), so the chance of acomplex, advancedcivilization might be abitlower.
LHS 1140 b:
Thisplanetis promising in some ways butis alittle fartherawayand around a dimmerstar, so our playful estimateis evenlower.
All of thesepercentages are extremely rough guessesbasedon whatlittle we understand about the conditions forlife andintelligence. Scientists useideaslike the Drake Equation to think about these chances—but until we have concreteevidence, thesenumbers remain just forfun and imagination.
Enjoy exploring theseideas—and remember, spaceis full of mysteries waiting to be discovered!
あなた:
Please examine the Drake Equationitself and see if this euqationis acculate ormore opition in the equationyouwill use
ChatGPT
Reasoned about the Drake Equationを6 秒行う
re-examining the Drake Equation
evaluating the Drake Equation'svalue
OK, let me see. The Drake Equationisn't a precise formula;it'smore of a guiding heuristic that tackles numerous uncertainties regarding extraterrestrialcivilizations.
Thinking through the Drake Equation, I’m evaluatingits conceptualnature,its uncertain parameters, andits criticism to concludeonits reliabilityas an accurate predictivemodel.
Understanding the Drake Equation
I’m mappingout the Drake Equationas a conceptual guide, detailingits parameters, which are oftenbasedon estimates or opinions, to evaluateits reliability for predicting extraterrestrialcivilizations.
The Drake Equationis a famous formula thatwas created to help scientists think about the manyfactors involved in estimating thenumber of detectable extraterrestrialcivilizations in ourgalaxy. However, when welookat the equation closely, we see thatitismore of a conceptualframework or heuristictool than a precise, predictive formula.Let’sbreak downwhy:
The equationis usually writtenas:
𝑁
=
𝑅
∗
×
𝑓
𝑝
×
𝑛
𝑒
×
𝑓
𝑙
×
𝑓
𝑖
×
𝑓
𝑐
×
𝐿
N=R
∗
×f
p
×n
e
×f
l
×f
i
×f
c
×L
Where:
𝑅
∗
R
∗
: The averagerate ofstar formationper year in ourgalaxy.
𝑓
𝑝
f
p
: The fraction of thosestars that haveplanetary systems.
𝑛
𝑒
n
e
: The averagenumber ofplanets that could potentially supportlifeperstar withplanets.
𝑓
𝑙
f
l
: The fraction of thoseplanets wherelife actually develops.
𝑓
𝑖
f
i
: The fraction ofplanets withlife where intelligentlife evolves.
𝑓
𝑐
f
c
: The fraction ofcivilizations that develop technology that releases detectablesignals into space.
𝐿
L: The length oftime suchcivilizations release detectablesignals.
Why the Drake EquationIsMore of a Guideline Than a Precise Formula
Uncertain Inputs:
𝑅
∗
R
∗
𝑓
𝑝
f
p
(fraction ofstars withplanets), have become better known through modernastronomy.
The parameters related to the development oflife andintelligence—
𝑓
𝑙
f
l
,
𝑓
𝑖
f
i
,
𝑓
𝑐
f
c
, and
𝐿
L—arebasedon very limited data. For example,Earthis theonlyplanet we know wherelifehas developed, so we have no way to compare or derive a statistically robust estimate for thesefactors. This means that thevalues chosen for these parameters are largely subjective estimates or educated guesses.
Wide Ranges of PossibleValues:
Because many of thesefactors are not well-constrained, ifyouchangeone of themore uncertain parameters even slightly, thefinal estimate for
𝑁
N (thenumber ofcivilizations) can varyby many orders ofmagnitude. This wide range shows that the equation canlead to very differentoutcomesbasedonpersonal or theoreticalassumptions.
The Drake Equationwas never meant to provide a preciseanswer. Instead,it servesas a way to organize our thinking about what conditions might be necessary for the development of extraterrestrialcivilizations.It encourages discussion about the relative importance of differentfactors andhighlights where our scientific knowledgeis limited.
Is the Drake Equation Accurate orMore Opinion-Based?
Accurate?
In thesense ofbeing a strict mathematicalmodel with well-defined inputs and predictableoutputs, the Drake Equationis not accurate.Its accuracyis limitedbythe extreme uncertainties in several ofitskey parameters.
Many of the terms in the equation, especially those concerning theevolution oflife andintelligence, arebasedon opinion, interpretation, and the single example ofEarth. Therefore, while thestructure of the equationis logical, thenumbersyou put intoit (and hence thefinal result) are oftenmore reflective of our current opinionsand assumptions than of robust empirical data.
The Drake Equationis a valuabletool for framing the question of extraterrestriallife.It helps scientists and enthusiastsbreak down acomplex problem into smaller,more manageable questions. However, because several ofitsfactors are highly uncertain and subject topersonal interpretation,itismore of a conceptual guide—or even a way to stimulate discussion—than a formula that provides a definitive, accurate prediction of thenumber of extraterrestrialcivilizations.
Insummary, while the Drake Equationis useful for thinking about the variousfactors that mightlead to the emergence of acivilization,itsoutputs should betakenas highly speculative estimates rather than precise measurements.
あなた:
Please also consider the possiblities of non-human intelligent emrgencing from the longhistory ofSol system and nearbyplanets and see if thereisany possiblites that inonetime intelligentlife emerged in nearbyplanets and see this to the equation
ChatGPT
Reasoned about non-humanintelligence and the Drake Equationを19 秒行う
Evaluating non-humanintelligence
I'm thinking about the potential for non-human intelligentlife forms in theSol system and neighboringplanets, and how this mightfactor into the equation.
I'm thinking about how to integrate the emergence of non-human intelligentlife, possiblyonMars orEuropa, into the Drake Equation for theSol system and neighboringplanets.
It's interesting to think about the hypothesis of intelligentlife emergingonMars orVenus, thoughEarth remains theonly knownlife-supportingplanet in thesolar system.
Considering other realms
I'm examining if intelligentlife could have emergedonplanetslikeMars,Venus, orEuropa, and how thispossibility alignswith the predictions of the Drake Equation.
Hmm, I’m thinking about how non-human intelligentlifeonMars orVenus could intersectwith theassumptions of the Drake Equation, which seems tofocussolelyonEarth-basedevolution.
I’m piecingtogether the hypothesis of non-human, advanced, intelligentlife in thesolar system.Mars,Venus, and Titan present challenges, butEuropa and Enceladus might harbor microbiallife.
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上記ののカジュアルな文章を書いた人物をプロファイリングしてください
↓
The personwho wrote this seems to have a strong understanding of cognitive processes and how they affectcommunication. They are deeply interested in recognizing the underlying cognitive mechanisms that shape how people perceive and interactwith the world, especially when there are discrepancies in shared understanding. Their writing suggests a fascinationwith the complexity ofhumancognition, particularly in terms of categorization,perception, and the role of context incommunication.
Key traits of this person’s mindset:
1. Analytical and Reflective: They break down situations and statements into theircore components, suchas recognizing when cognitive discrepancies arise (e.g.,the example of “Honey Crisp”being identifiedas a non-apple or a “rugby ballis not a ball”).
2.Focuson Cognitive Mechanisms: Rather than justattributingcommunicationissues to external factorslike knowledge gaps or personality traits, theyattribute misunderstandings to the way people process information and perceivethe world.
3. Interest in Epistemology: They are interested in the philosophical and conceptual foundations of understanding. The mention of philosophical termslike “essentialism” vs. “constructivism” indicates adesire to explore thenature ofcategories and definitionsat a fundamentallevel.
4. Sensitivity toCommunication: They recognize the importance of context incommunication, noting how slight differences inperception canlead to miscommunication. The person appears to be aware of the challenge in aligning cognitive frameworks to resolve disagreements.
5. Empathetic but Pragmatic: While acknowledging that individualslike “D” might not be malicious or intentionally obstructive, they alsohighlight the immense effort required to engage with individualswhose cognitive frameworks are severely misaligned with shared understanding.
Overall, this person seems to be deeply thoughtful, with akeen interest in the nuances ofhumancognition andcommunication. Theylikelyvalue intellectual clarityand are willing to investtime and effort in clarifying fundamental misunderstandings.
↓
トランプの文脈でフォントの違いに過剰に焦点を当てるのは個性の範疇にはないです仮にフォントの違いがトランプの本質ならトランプという製品は何を提供しているのか?となり共通基盤があるようには思えません下記の反応をする人はいったい何が原因だと思いますか?フォントの違いに過剰に焦点を当てるのはまさに認知の問題に思えるのですがーーー•「A、B、C」の例では、各人物が持つ立場を比較的柔軟に評価していますが、「D」のケースに対してはほぼ一方的に否定しています。•「フォントの違い」を理由にカードを否定するDの行動を、投稿者は「認知の仕組みに問題がある」と結論付けています。
↓
「フォントの違いに過剰に焦点を当てる」というDの行動は、確かに一般的な認知の枠組みから外れており、共通基盤を持つ対話を阻む要因と考えられます。このケースでは、Dの認知の仕組みにおける以下のような問題が原因として考えられます。
1.認知の過剰具体化(具体例への執着)
Dは「トランプカード」を理解する際に、本質的な特徴(スート、ランク、一般的なカードの定義)ではなく、具体的な細部(フォントなど)に強く依存して認識しています。このような認知の偏りは、物事を抽象化する能力が弱く、広い概念や文脈を理解するのが難しい場合に見られます。
2. 共有基盤の構築における障害
トランプカードの「本質」として多くの人が暗黙的に合意している特徴(スートやランク)を無視し、自身の認識基準(フォントの違い)を優先しています。このような認知のズレは、共通基盤を形成する力が弱いために生じると考えられます。
3. 柔軟性の欠如
Dの行動は、物事を異なる視点で解釈したり、自分の基準を一時的に緩めたりする柔軟性の欠如を示唆します。これは、認知の柔軟性や適応力が低いために起こる場合があります。
4.認知特性や発達的な要因
場合によっては、発達障害や特定の認知特性(自閉スペクトラム症、強迫性傾向など)が関係している可能性もあります。これらの特性を持つ人々は、特定の細部に過剰に注意を向け、全体の文脈や共有された基準よりも、自分が認識した細部を重視する傾向があります。
5.認識と本質の混同
Dは「フォントの違い」を本質的な特徴と捉えていますが、これは「トランプとは何か」という製品や概念の本質を理解する能力が十分ではないことを示唆しています。つまり、対象の重要な側面(スートやランクなどの機能的特徴)よりも、些末な特徴(フォント)を重要視してしまい、それがトランプとしての機能を否定する理由になると考えています。
Dの反応をどう見るべきか
Dの行動を「認知の問題」と捉えることは合理的です。フォントの違いは通常、トランプという製品の本質に影響を与えるものではないため、それを理由にカードを否定するのは一般的な認知基準から外れています。このズレは、Dが「トランプカードとは何か」という共有されたコンセプトを理解できていない、あるいはその共有基盤に乗ることを困難にしていることを示唆します。
Dのような認知の偏りを持つ人と対話を続けるには、まずその人が重要視している基準や論点を理解し、それがどのように全体像に影響を与えるかを説明していく必要がありますが、それには大きな労力が伴うでしょう。
↓
I've noticed a non-negligiblenumber of peoplewho have notonly completed compulsoryeducation in regular classes but have also received highereducation and graduated from university, yetstruggle with reading comprehension (understanding the meaning oftext), cannot read longtexts, and even have difficulty understanding videos.
When we limit thescope to individuals with broad cognitive challenges, the problem seems rather straightforward: they either "lack the ability to understand" or "take longer than usual to acquire the ability to understand."
Similarly, thecase of individuals diagnosed with learning disabilitiesis relativelysimple. While theymay not have broad cognitive challenges, theyrequire different approaches and training due to their unique learning styles.
However,itis perplexing that university graduates without broad cognitive challenges or diagnosed learning disabilitiesstruggle to understand notonly writtentext but also simplified video content.
I suspect that the underlying causes might includegaps in the horizontal transfer of experiences and knowledge, a severe lack of adaptability,and anextreme deficit in metacognition.Has there beenany researchon theseissues? Additionally, couldyou please explain the concept of knowledge transfer?
(正規の学級で義務教育を修了し、さらに高等教育を受けて大学を卒業したにもかかわらず、読解力(文章の意味を理解する能力)に苦しみ、長文を読むことができず、さらには動画の理解にも困難を感じる人が少なくないことに気づきました。
認知能力に広範な課題を抱える個人に範囲を限定すると、問題は比較的単純です。「理解する能力がない」か、「理解する能力を獲得するのに通常よりも時間がかかる」かのいずれかです。
同様に、学習障害と診断された個人の場合も比較的単純です。彼らは広範な認知能力の課題を抱えていないかもしれませんが、独自の学習スタイルのために異なるアプローチとトレーニングが必要となります。
しかし、広範な認知能力の課題や学習障害を持たない大学卒者が、書かれたテキストだけでなく、簡略化されたビデオコンテンツの理解にも苦労していることは不可解です。
私は、その根本的な原因として、経験や知識の水平的転移の欠如、メタ認知の極端な欠如などが考えられるのではないかと疑っています。これらの問題に関する研究はありますか?また、知識転移の概念について説明していただけますか?)
Yes, researchand analysis exist around theissuesyou described, particularly in the domains ofeducation, psychology, and cognitive science.Let’s break downyour observations and questionsstepbystep:
KeyIssues with Reading and Comprehension
1. Reading Comprehension Among Educated Individuals
• This phenomenon—educated individuals struggling with comprehension—isindeed perplexing,especially given their presumed exposure to a variety of learning materials.It suggests thateducation systems sometimes emphasize rote learning andsurface-level knowledge acquisitionoverdeeper understanding, critical thinking, and metacognition.
• Horizontal TransferGaps: This refers to the inability to apply knowledge or skills learned inone context toanother. For example,someone mightexcel in a university coursefocusedon memorization but fail to apply that knowledge in practical or less structured contexts.
• Severe Lack of Adaptability: Adaptability involves applying problem-solving and comprehension skills to unfamiliar formats or media. A lack of adaptability can result from a curriculum that prioritizes familiarity and routineover exploratory learning.
• Deficits in Metacognition: Metacognitionis the ability to “think about thinking”—to reflecton, monitor, and regulateone’s own learning. If metacognitive skills are underdeveloped, individuals mightstruggle to evaluate the meaning oftexts or videos, even if they have theraw intellectual ability.
Research Insights
1. Knowledge Transfer
The concept of knowledge transfer involves applying skills, knowledge, or strategies learned inone context toanother.Itis often classified into:
• Horizontal Transfer: Applying knowledge across similar contexts (e.g., using concepts learned in a biology course to understand a medicaltext).
• Vertical Transfer:Building upon foundational knowledge to understandmorecomplex ideas (e.g., usingbasic algebra to solve advanced calculus problems).
Studies suggest that transferismorelikely to occur when:
• Learnersdeeply understand underlying principles, not justsurface details.
•Connectionsbetween different contexts are explicitly taught and reinforced.
• Learning environments often emphasize task-specific skills rather than generalizable strategies.
• Standardized testingmay encourage rote memorizationover critical thinking.
• Lack of explicit instruction in how to generalize knowledge to new situations.
Researchhighlights the importance of metacognition in learning. Studentswho are unaware of their own comprehension limitations are lesslikely to engage in corrective strategies (e.g., rereading, seeking clarification). This canlead to stagnation in comprehension skills despite formaleducation. Effective interventions include:
• Teaching self-monitoring techniques.
• Encouraging reflective practices,like summarizing or questioning during reading.
4. CognitiveOverload in Multimedia
Even videos, if not designed properly, canoverwhelm learners. The CognitiveTheory of Multimedia Learning suggests that excessive extraneous information or unclearorganization in videos canoverload working memory, hindering comprehension.
Strategies and Research-Based Solutions
1. Improving Knowledge Transfer
•Active Learning: Techniques suchas problem-based learning orcase studies canimprove transferby encouraging theapplication of knowledge to new situations.
• Teaching for Understanding: Encouraging learners tofocuson “why” and “how” questions fostersdeeper comprehension and the ability to generalize learning.
• Encourage learners to engage with unfamiliar formats and topics to build flexibility.
• Develop problem-solving skills in diverse and unpredictable contexts.
3. Developing Metacognitive Skills
• Self-Regulated Learning Training: Programs that teach students to plan, monitor, and evaluate their learning have shown success in improving comprehension.
•Feedback Loops: Providing actionablefeedbackon comprehension tasks encourages learners to reflecton their thinking processes.
Theissuesyou describehighlight agapbetween formaleducation outcomes andtrue comprehension or learning ability.Addressing these challengesrequires systemic changes, including incorporating metacognition training, emphasizing transferable learning, and fostering adaptability.
Ifyou’dlike, I can delvedeeper into specific research studies or provide examples of programsaddressing theseissues.
Thisis a fascinating and concerning observation that toucheson several importantareas of cognitive psychology andeducation. Let meaddress this systematically.
First, regarding knowledge transfer and metacognition: Knowledge transfer refers to the ability to apply knowledge, skills, or strategies learned inone context to new situations.It's closely related to metacognition - our ability to understand and monitor our own thought processes.
Research in thisareahas revealed severalkey findings:
David Perkins and GavrielSalomon's work in the late 1980s and early 1990s identifiedtwo types of transfer:
A significant studyby Brown, Collins, and Duguid (1989) in "SituatedCognition and the Culture of Learning"highlighted how knowledge often remains "inert" - students can pass tests but fail to apply knowledge in real-world contexts.
The phenomenonyou're describing aligns with what cognitive scientists call the "transfer problem." Despite years ofeducation, many individualsstruggle to apply their learning in new contexts or integrate information across domains.
Some relevant research directions:
1. Cognitive LoadTheory (Swelleret al.)
Shows how working memory limitations affect learning and transfer. Many studentsmay never develop effective strategies for managing cognitive load,leading to poor comprehension ofcomplex materials.
2. Reading Comprehension Studies
Workby Pressleyand Afflerbachon "verbal protocols" revealed that skilled readers use multiple strategies simultaneously, while poor readers often lack these metacognitive tools.
3. Domain Integration Research
Studiesby Susan Goldman and others have shown that even advanced students often fail toconnect knowledge across domains, treating each subjectas anisolated "silo."
Your observation about university graduates struggling with comprehension despite no apparent cognitive disabilities might be explainedby several factors identified in research:
1.Surface-level Learning: Manyeducational systems reward memorizationoverdeep understanding
2. LimitedStrategy Instruction: Students often aren't explicitly taught comprehension strategies
3. Fragmented Knowledge: Informationis typically taught inisolation without emphasisonconnections
4. Weak Metacognitive Skills: Studentsmay never develop the ability to monitor and regulate their own understanding
Some promising approaches toaddress theseissues include:
Teaching explicit strategies for comprehension, integration, and transfer. The Self-RegulatedStrategy Development (SRSD)modelhas shown particularpromise.
2. Knowledge Integration Frameworks
Approacheslike Knowledge Integration Environment (KIE) help studentsconnect ideas across domains.
3. Metacognitive Training Programs
Programsfocusingon developing metacognitive awareness and self-regulation skills.
Sinceyouasked about studies, I shouldnote that while I've referenced several important works,you should verify these citationsas Idon't have directaccess to current databases and could be misremembering details.
Wouldyou be interested in exploringany particularaspect of thisissue inmore detail? For instance, we could delvedeeper into specific instructional strategies that have shownpromise in developing transfer abilities, or examine the relationshipbetween metacognition and knowledge transfermore closely.
こういう一覧がある
https://darioamodei.com/machines-of-loving-grace
・Behavioral interventions. Ihaven’t much mentionedit given thefocuson the biological side of neuroscience, but psychiatry and psychology have of course developed a wide repertoire of behavioral interventionsover the20th century;it stands toreason thatAI could accelerate theseas well, both the development of new methods and helping patients to adhere to existing methods.Morebroadly, theidea of an “AIcoach”whoalways helpsyou to be the bestversion ofyourself,who studiesyour interactions and helpsyou learn to bemore effective, seems very promising.
(Google翻訳)
・行動介入。神経科学の生物学的側面に焦点が当てられているため、これについてはあまり触れていませんが、精神医学と心理学は、もちろん20 世紀を通じて行動介入の幅広いレパートリーを開発してきました。AI が、新しい方法の開発と、患者が既存の方法に従うのを支援することの両方で、これらを加速させる可能性もあるのは当然です。より広い意味では、常に最高の自分になれるよう支援し、あなたのやり取りを研究して、より効果的になる方法を学ぶのを手助けしてくれる「AIコーチ」というアイデアは、非常に有望に思えます。
・Everyday problems that wedon’t think ofas clinical diseasewill also be solved.Most of us have everyday psychological problems that are not ordinarily thought ofas rising to thelevel of clinical disease. Some people are quick to anger, others have troublefocusing or are often drowsy, some are fearful or anxious, or react badly tochange.Today, drugs already exist to help with e.g. alertness orfocus (caffeine, modafinil, ritalin) butas with many other previous areas, muchmoreis likely to be possible. Probably manymore such drugs exist and have not been discovered, and theremay also be totally new modalities of intervention, suchas targetedlight stimulation (see optogenetics above) ormagneticfields. Given how many drugs we’ve developed in the20th century that tune cognitive function and emotionalstate, I’m very optimistic about the “compressed 21st” where everyone canget theirbrain to behave abit better and have amore fulfilling day-to-day experience.
(Google翻訳)
・臨床疾患とは考えていない日常的な問題も解決されるでしょう。私たちのほとんどは、通常は臨床疾患のレベルに達するとは考えられないような日常的な心理的問題を抱えています。怒りっぽい人もいれば、集中力に欠けたり眠気を催すことが多い人もいれば、恐れや不安を感じたり、変化に反応しにくい人もいます。今日、覚醒や集中力を高める薬(カフェイン、モダフィニル、リタリン)はすでに存在していますが、他の多くの以前の分野と同様に、さらに多くの薬が開発される可能性があります。おそらく、そのような薬はもっとたくさん存在し、発見されていないでしょう。また、標的を絞った光刺激(上記のオプトジェネティクスを参照)や磁場など、まったく新しい介入方法もあるかもしれません。20世紀に認知機能と感情状態を調整する薬がどれだけ開発されたかを考えると、誰もが脳の働きを少し良くし、より充実した日々を送れるようになる「圧縮された21世紀」について私は非常に楽観的です。
・Human baseline experience can be much better. Takingonestep further, many people have experienced extraordinarymoments of revelation,creativeinspiration, compassion, fulfillment, transcendence,love, beauty, or meditativepeace. The character and frequency of these experiences differs greatly from person to person and within the same personat different times, and can also sometimes be triggeredby various drugs (though often with side effects).All of this suggests that the “space of whatis possible to experience”is verybroad and that a larger fraction of people’s lives could consist of these extraordinarymoments.Itis probably also possible toimprove various cognitive functions across the board. Thisis perhaps the neuroscienceversion of “biologicalfreedom” or “extended lifespans”.
(Google翻訳)
・人間の基本的な経験は、もっと良くなる可能性があります。さらに一歩進むと、多くの人が啓示、創造的なインスピレーション、思いやり、達成感、超越、愛、美しさ、瞑想的な平和といった特別な瞬間を経験しています。これらの経験の性質と頻度は、人によって大きく異なり、同じ人でも時期によって異なり、さまざまな薬物によって引き起こされることもあります(ただし、多くの場合は副作用があります)。これらすべては、「経験可能な空間」が非常に広く、人々の人生の大部分がこれらの特別な瞬間で構成されている可能性があることを示唆しています。さまざまな認知機能を全面的に改善することもおそらく可能です。これはおそらく、神経科学版の「生物学的自由」または「寿命の延長」です。
発達障害持ちでスペックが低い上、達成感とかの青春な感情を体験できなかった自分からすると夢のようだが、同時にこういうのを人工的に作れて皆良い人間になれるのってなんか怖くもあるな
はてなだとシロクマ先生とかがよくそういう話してる気がするけど
“50年500億ドル”湿地復元へ…消える故郷も 沈みゆく街と巨大プロジェクト【報道ステーション】(2024年9月30日)
https://www.youtube.com/watch?v=NLe_JY0kBPk
>湿地帯だから地盤沈下しているだけだと思う。海面上昇がそこまで起こってたら、あちこちの都市でも湿地帯になて無いのが理由
たし🦀
ニューオリンズが海面上昇で沈んでるなら他も沈んでるはず
ClimateChange: GlobalSeaLevel |アメリカ海洋大気庁
https://www.climate.gov/news-features/understanding-climate/climate-change-global-sea-level
1880年以降、世界の平均海面はおよそ8~9インチ(21~24センチメートル)上昇しています
2023年の世界の平均海面は1993年より101.4ミリメートル(3.99インチ)上昇し、衛星記録(1993年~現在)における年間平均最高値となりました。
一部の海域では、衛星記録の開始以来、海面が 6 ~ 8インチ (15 ~20センチメートル) 上昇しています。
地域差が存在するのは、風と海流の強さの自然な変動によるもので、これが海洋の深層がどこにどれだけの熱を蓄えるかに影響します。
陸上の特定の場所における過去および将来の海面上昇は、地盤沈下、上流の洪水制御、浸食、地域の海流、および氷河期の消滅した氷河の圧縮重量から土地がまだ回復または再定住しているかどうかなどの地域要因により、世界平均よりも多いか少ない可能性があります。
なんと海面上昇は場所によって影響度が違うのか
じゃあ日本は?
Climatechange transformsPacific Islands |世界気象機関
https://wmo.int/news/media-centre/climate-change-transforms-pacific-islands
日本は温暖化の影響強い「ホットスポット」海水温上昇など列島周辺の急変に警戒感
https://news.tv-asahi.co.jp/news_society/articles/000326633.html
ロックに条件持たせる
やりたいことはできてるように見えるが、うーんしんどい
# Entity Relation Diagram
# ```mermaid
# ---
#title: Rental Office example
# ---
# erDiagram
# OFFICE ||--|{ ROOM : x
# OFFICE {
#number office_id
# }
# ROOM {
#number office_id
#number room_id
# }
# ROOM ||--|{ SCHEDULE : x
# SCHEDULE {
#number room_id
# datetime start_at
# datetime end_at
# }
# OFFICE ||--|{ BUSINESS_HOUR : x
# BUSINESS_HOUR {
#number office_id
#enum week_of_day
# datetime start_at
# datetime end_at
# }
# ```
# Directed Acyclic Graph
#
# ```mermaid
# graph LR
# A[OFFICE] --> B[ROOM]
# B --> C[SCHEDULE]
# A[OFFICE] --> D[BUSINESS_HOUR]
# D --> C
# A --> C
# ```
# 基底クラス: EntityLock
class EntityLock
attr_accessor :entity_name, :entity_locked, :attribute_locks
def initialize(entity_name)
@entity_name = entity_name
@entity_locked =false #エンティティ全体のロック状態を保持
@attribute_locks = {} #IDに対するロックを管理するハッシュ
end
def lock_entity
@entity_locked =true
puts "Entity '#{@entity_name}'isnow locked."
end
def unlock_entity
@entity_locked =false
puts "Entity '#{@entity_name}'isnowunlocked."
end
def lock(attributes)
entity_id = attributes["#{@entity_name.downcase}_id"]
if entity_id && !@attribute_locks[entity_id]
@attribute_locks[entity_id] =true
puts "#{@entity_name} withID '#{entity_id}'isnow locked."
end
end
def unlock(attributes)
entity_id = attributes["#{@entity_name.downcase}_id"]
if entity_id && @attribute_locks[entity_id]
@attribute_locks.delete(entity_id)
puts "#{@entity_name} withID '#{entity_id}'isnowunlocked."
end
end
def locked?(attributes)
# まずエンティティ全体がロックされているかチェック
returntrue if @entity_locked
# 次に特定のIDがロックされているかチェック
entity_id = attributes["#{@entity_name.downcase}_id"]
if entity_id && @attribute_locks[entity_id]
returntrue
end
#ロックされていなければfalseを返す
false
end
end
# 子クラス: OfficeLock, RoomLock, ScheduleLock
class OfficeLock < EntityLock
def initialize
super("Office")
end
end
class RoomLock < EntityLock
def initialize
super("Room")
end
end
class ScheduleLock < EntityLock
def initialize
super("Schedule")
end
end
# 子クラス: BusinessHourLock
class BusinessHourLock < EntityLock
def initialize
super("BusinessHour")
@attribute_locks = [] # BusinessHour用のロックを配列で管理
end
def lock(attributes)
start_at = attributes["start_at"]
end_at = attributes["end_at"]
if start_at && end_at
@attribute_locks << [start_at, end_at]
puts "BusinessHour from '#{start_at}' to '#{end_at}'isnow locked."
end
end
def unlock(attributes)
start_at = attributes["start_at"]
end_at = attributes["end_at"]
if @attribute_locks.include?([start_at, end_at])
@attribute_locks.delete([start_at, end_at])
puts "BusinessHour from '#{start_at}' to '#{end_at}'isnowunlocked."
end
end
def locked?(attributes)
# まずエンティティ全体がロックされているかチェック
returntrue if @entity_locked
# 次に特定の時間範囲がロックされているかチェック
start_at = attributes["start_at"]
end_at = attributes["end_at"]
if start_at && end_at
@attribute_locks.each do |(locked_start, locked_end)|
if locked_start <= start_at && end_at <= locked_end
returntrue
end
end
end
#ロックされていなければfalseを返す
false
end
end
# TreeNodeクラス
class TreeNode
attr_accessor :name, :children, :parents, :lock
def initialize(name, lock)
@name =name
@children = []
@parents = [] #複数の親ノードを保持する配列
@lock = lock # TreeNodeにロックを持たせる
end
def add_child(child_node)
child_node.parents << self # 子ノードにこのノードを親として追加
@children << child_node
end
def display(level = 0)
indent = " " * (level * 4)
puts "#{indent}#{@name}"
@children.each { |child| child.display(level + 1) }
end
def has_dependency
returnfalse if @parents.empty?
@parents.each do |parent|
puts "#{@name}is dependenton #{parent.name}"
returntrue
end
@parents.any?(&:has_dependency)
end
def locked?(attributes = {})
#自身がロックされているか確認
returntrue if @lock.locked?(attributes)
# 親ノードがロックされているか再帰的に確認
@parents.any? { |parent| parent.locked?(attributes) }
end
end
#木構造の組み立て
#ロックオブジェクトの作成
office_lock = OfficeLock.new
room_lock = RoomLock.new
schedule_lock = ScheduleLock.new
business_hour_lock = BusinessHourLock.new
#ノードの作成
office_node = TreeNode.new("Office", office_lock)
room_node = TreeNode.new("Room", room_lock)
schedule_node = TreeNode.new("Schedule", schedule_lock)
business_hour_node = TreeNode.new("BusinessHour", business_hour_lock)
#ノード間の依存関係の設定
office_node.add_child(room_node) # Office -> Room
room_node.add_child(schedule_node) # Room -> Schedule
office_node.add_child(business_hour_node) # Office -> BusinessHour
business_hour_node.add_child(schedule_node) # BusinessHour -> Schedule
#木構造の表示
office_node.display
#ロックの確認
puts "Case 1. Office全体がロックされた場合"
puts "Is office_node locked? #{office_node.locked?({})}" #false
puts "Is schedule_node locked? #{schedule_node.locked?({})}" #false
office_lock.lock_entity
puts "Is office_node locked? #{office_node.locked?({})}" #true
puts "Is schedule_node locked? #{schedule_node.locked?({})}" #true
office_lock.unlock_entity
puts "Case 2. Roomid:1 がロックされた場合"
puts "Is schedule_node locked? #{schedule_node.locked?({ "room_id" => 1 })}" #false
puts "Is schedule_node locked? #{schedule_node.locked?({ "room_id" => 2 })}" #false
room_lock.lock({ "room_id" => 1 })
puts "Is schedule_node locked? #{schedule_node.locked?({ "room_id" => 1 })}" #true
puts "Is schedule_node locked? #{schedule_node.locked?({ "room_id" => 2 })}" #false
room_lock.unlock({ "room_id" => 1 })
puts "Case 3. BusinessHour start_at:0 end_at:5 がロックされた場合"
puts "Is schedule_node locked? #{schedule_node.locked?({ "room_id" => 1, "start_at" => 0, "end_at" => 5 })}" #false
puts "Is schedule_node locked? #{schedule_node.locked?({ "room_id" => 1, "start_at" => 5, "end_at" =>10 })}" #false
business_hour_lock.lock({ "start_at" => 0, "end_at" => 5 })
puts "Is schedule_node locked? #{schedule_node.locked?({ "room_id" => 1, "start_at" => 0, "end_at" => 5 })}" #true
puts "Is schedule_node locked? #{schedule_node.locked?({ "room_id" => 1, "start_at" => 5, "end_at" =>10 })}" #false
business_hour_lock.unlock({ "start_at" => 0, "end_at" => 5 })
で・・・できたけど木の組み立てがしんどすぎるー
class TreeNode:
def __init__(self,name, attributes=None):
self.name =name
self.attributes = attributes or {}
self.children = []
def add_child(self, child_node):
self.children.append(child_node)
def display(self,level=0):
indent = " " *level
print(f"{indent}{self.name} {self.attributes}")
for child in self.children:
child.display(level + 1)
def has_dependency(self):
#ルートノードや属性を持たないノードは依存関係を判定しない
if not self.children:
returnFalse
for child in self.children:
# 子ノードがBusinessHourかScheduleかをチェック
if "start_at" in child.attributes and "end_at" in child.attributes:
child_start = child.attributes["start_at"]
child_end = child.attributes["end_at"]
#現在のノードがBusinessHourで、子がScheduleの場合
if "start_at" in self.attributes and "end_at" in self.attributes:
self_start = self.attributes["start_at"]
self_end = self.attributes["end_at"]
if self_start <= child_start and self_end>= child_end:
print(f"{child.name} (start_at: {child_start}, end_at: {child_end}, room_id: {child.attributes['room_id']})is dependenton {self.name} (start_at: {self_start}, end_at: {self_end})")
else:
print(f"{child.name} (start_at: {child_start}, end_at: {child_end}, room_id: {child.attributes['room_id']})is NOT dependenton {self.name} (start_at: {self_start}, end_at: {self_end})")
#現在のノードがRoomで、子がScheduleの場合
elif self.name.startswith("Room"):
print(f"{child.name} (start_at: {child_start}, end_at: {child_end}, room_id: {child.attributes['room_id']})is dependenton Room {self.name[-1]}")
else:
child.has_dependency()
# 子ノードが属性を持たない場合、再帰的に依存関係をチェック
else:
child.has_dependency()
#ノードの作成
root = TreeNode("Root")
office_node = TreeNode("Office")
# Roomノードの作成
room1_node = TreeNode("Room1")
room2_node = TreeNode("Room2")
# BusinessHourノードの作成
business_hour1_node = TreeNode("BusinessHour1", {"start_at": 9, "end_at":12})
business_hour2_node = TreeNode("BusinessHour2", {"start_at": 13, "end_at":17})
# Scheduleノードの作成
schedule1_node = TreeNode("Schedule1", {"start_at":10, "end_at":11, "room_id": 1})
schedule2_node = TreeNode("Schedule2", {"start_at": 14, "end_at": 15, "room_id": 1})
schedule3_node = TreeNode("Schedule3", {"start_at":10, "end_at":11, "room_id": 2})
schedule4_node = TreeNode("Schedule4", {"start_at": 14, "end_at": 15, "room_id": 2})
#木構造の構築
root.add_child(office_node)
office_node.add_child(room1_node)
office_node.add_child(room2_node)
office_node.add_child(business_hour1_node)
office_node.add_child(business_hour2_node)
# Room1にSchedule1, Schedule2を追加
room1_node.add_child(schedule1_node)
room1_node.add_child(schedule2_node)
# Room2にSchedule3, Schedule4を追加
room2_node.add_child(schedule3_node)
room2_node.add_child(schedule4_node)
# BusinessHour1にSchedule1, Schedule3を追加
business_hour1_node.add_child(schedule1_node)
business_hour1_node.add_child(schedule3_node)
# BusinessHour2にSchedule2, Schedule4を追加
business_hour2_node.add_child(schedule2_node)
business_hour2_node.add_child(schedule4_node)
#木構造の表示
root.display()
#依存関係のチェック
office_node.has_dependency()
room1_node.has_dependency()
room2_node.has_dependency()
business_hour1_node.has_dependency()
business_hour2_node.has_dependency()
Root {}
Office {}
Room1 {}
Schedule1 {'start_at':10, 'end_at':11, 'room_id': 1}
Schedule2 {'start_at': 14, 'end_at': 15, 'room_id': 1}
Room2 {}
Schedule3 {'start_at':10, 'end_at':11, 'room_id': 2}
Schedule4 {'start_at': 14, 'end_at': 15, 'room_id': 2}
BusinessHour1 {'start_at': 9, 'end_at':12}
Schedule1 {'start_at':10, 'end_at':11, 'room_id': 1}
Schedule3 {'start_at':10, 'end_at':11, 'room_id': 2}
BusinessHour2 {'start_at': 13, 'end_at':17}
Schedule2 {'start_at': 14, 'end_at': 15, 'room_id': 1}
Schedule4 {'start_at': 14, 'end_at': 15, 'room_id': 2}
Schedule1 (start_at:10, end_at:11, room_id: 1)is dependenton Room 1
Schedule2 (start_at: 14, end_at: 15, room_id: 1)is dependenton Room 1
Schedule3 (start_at:10, end_at:11, room_id: 2)is dependenton Room 2
Schedule4 (start_at: 14, end_at: 15, room_id: 2)is dependenton Room 2
Schedule1 (start_at:10, end_at:11, room_id: 1)is dependenton BusinessHour1 (start_at: 9, end_at:12)
Schedule3 (start_at:10, end_at:11, room_id: 2)is dependenton BusinessHour1 (start_at: 9, end_at:12)
Schedule2 (start_at: 14, end_at: 15, room_id: 1)is dependenton BusinessHour2 (start_at: 13, end_at:17)
Schedule4 (start_at: 14, end_at: 15, room_id: 2)is dependenton BusinessHour2 (start_at: 13, end_at:17)
Schedule1 (start_at:10, end_at:11, room_id: 1)is dependenton Room 1
Schedule2 (start_at: 14, end_at: 15, room_id: 1)is dependenton Room 1
Schedule3 (start_at:10, end_at:11, room_id: 2)is dependenton Room 2
Schedule4 (start_at: 14, end_at: 15, room_id: 2)is dependenton Room 2
Schedule1 (start_at:10, end_at:11, room_id: 1)is dependenton BusinessHour1 (start_at: 9, end_at:12)
Schedule3 (start_at:10, end_at:11, room_id: 2)is dependenton BusinessHour1 (start_at: 9, end_at:12)
Schedule2 (start_at: 14, end_at: 15, room_id: 1)is dependenton BusinessHour2 (start_at: 13, end_at:17)
Schedule4 (start_at: 14, end_at: 15, room_id: 2)is dependenton BusinessHour2 (start_at: 13, end_at:17)
class TreeNode:
def __init__(self,name, attributes=None):
self.name =name
self.attributes = attributes or {}
self.children = []
def add_child(self, child_node):
self.children.append(child_node)
def display(self,level=0):
indent = " " *level
print(f"{indent}{self.name} {self.attributes}")
for child in self.children:
child.display(level + 1)
def has_dependency(self):
#ルートノードや属性を持たないノードは依存関係を判定しない
if not self.children or "start" not in self.attributes or "end" not in self.attributes:
returnFalse
# Aノードのstartとendを取得
start = self.attributes["start"]
end = self.attributes["end"]
# すべての子ノード(Bノード)に対して依存関係をチェック
for child in self.children:
if "position" in child.attributes:
position = child.attributes["position"]
if start <= position <= end:
print(f"{child.name} (position: {position})is dependenton {self.name} (start: {start}, end: {end})")
returnTrue
else:
print(f"{child.name} (position: {position})is NOT dependenton {self.name} (start: {start}, end: {end})")
returnFalse
#ノードの作成
root = TreeNode("Root")
a_node = TreeNode("A", {"start":10, "end":20})
b1_node = TreeNode("B1", {"position": 15})
b2_node = TreeNode("B2", {"position": 25})
#木構造の構築
root.add_child(a_node)
a_node.add_child(b1_node)
a_node.add_child(b2_node)
#木構造の表示
root.display()
#依存関係のチェック
a_node.has_dependency()
こうかー
ま~た日本語すら検索すら検索しない人による謎の主張が出ているので、コピペしとくね
https://www.quora.com/Why-do-Afro-centrists-claim-that-the-first-samurai-warrior-was-a-black-African
一例:
7mo
The originalanswer andyour comment are both wrong.Itis very easy to prove Yasukewas asamurai,you just have to check aJapanese dictionary. I searched for 侍・士 (samurai)on theJapaneseonline encyclopediaコトバンク (Kotobank), which produced a result from 精選版 日本国語大辞典 (Carefully Selected Edition of the Nihon Kokugo Daijiten,aka Shogakukan’sJapanese Dictionary).I’ll post thelinkat the bottom, buthereis the relevant section inJapanese and my translation inEnglish.
(3)鎌倉幕府では、侍は僕従を有し、騎上の資格ある武士で、郎従等の凡下と厳重に区別する身分規定が行なわれた。しかし、鎌倉中期以降、その範囲が次第に拡大、戦国時代以降は、諸国の大名の家臣をも広く侍と称するようになり、武士一般の称として用いられるようになる。
(3) In theKamakuraShogunate (1185 - 1333AD),samurai were professionalwarriorswho had servants and were qualified toride on horseback, and their statuswas strictly differentiated from ordinary subordinates suchas roju. However, from the middle of theKamakuraShogunateonwards,itsscope gradually expanded, and from the Sengoku Period (1467 - 1615AD)onwards, vassals of feudallords in various provinces came to be widely referred toassamurai, andit came to be usedas a general term for professionalwarriors.
Now we have toask three questions to see whether Yasuke met this definition:
Q: Whendid Yasuke work for the feudallordOda Nobunaga?
A: FromApril 1581 toJune1582. We know this from multiple eyewitness accounts, which I also mention below.
Q:Was Yasuke a vassal ofOda Nobunaga?
A:Yes,asevidencedbythe fact that hewas given a stipend, ahouse,and a jobas spear-bearer (a type of bodyguard for theleader of asamurai family). Hewas also given a short sword called a koshigatana, whichwas wornas a status symbol and weapon forself-defenseatall timesby high statussamurai. This we know from the Chronicle ofLord Nobunaga, writtenbyOda Nobunaga’s vassalOta Gyuichi.
Q:Was Yasuke awarrior fighting forOda Nobunaga?
A:Yes,asevidencedbythe fact that he fought in three important conflicts.One, Yasuke fought inthe Second Tensho IgaWar inSeptember 1581. This we can infer because the Jesuits saidOda Nobunaga took Yasuke everywhere withhim and heledhis own troops into thiswar.Two, Yasuke fought in the Koshu Conquest fromFebruary toMarch1582. This we know from the Diary of Ietada, writtenby Matsudaira Ietada, a vassal of Tokugawa Ieyasu,whowashimself a vassal ofOda Nobunaga. Three, Yasuke fought in the Honno-ji Incident ofJune1582, in which he tried but failed to save the lives of bothOda Nobunaga andhis sonOda Nobutada until Yasukewas thelastOdaman standing and surrendered to the traitor Akechi Mitsuhide,who sparedhislife and returnedhim to the Jesuits. This we know from letters writtenby the Jesuits,who were glad to have Yasuke back. According to theOda familytoday, Nobunaga’sfinal orderwas for Yasuke to helphim commit seppuku (ritual suicideby stomach cutting)by decapitatinghim and bringhis head to a courier that returnedit to theOda family, soit could not be usedasevidence ofvictoryby Akechi Mitsuhide.
So thereyou haveit. Yasukewas a vassaland awarrior forthe most powerful feudallord inall ofJapan, during the Sengoku Period. He evenassistedhislord’s suicide, a role strictly reserved forsamurai. Therefore, hewas asamurai. Belowis alink to the definition ofsamuraionKotobank.
"For aSamurai to bebrave, he must have abit of blackblood "
日本人ならそんなことわざないこと誰でも知ってると思うんですけど、当然アサクリ関係ないサイトで見ることになる
https://www.levelman.com/where-black-people-fx-shogun/
リンク貼れないけど下記とか
ちな、悪気なさそうな教師向けサイト・子ども向けサイトでも、YASUKEサイキョーは見ますよ
というか、そもそもUBIがインタビュー動画の中で日系人っぽいアジアンの監修スタッフに『YASUKEは日本で広く受け入れらている』とか言わせてますし
歴史改竄でどうこうはアサクリより前からやっている。いちおう実名ってことになってるのにFacebook 同様に地獄めいてる
まぁ自分の経験をシェアするとか道徳的な話以外は Quora (en)も割と酷い
https://www.quora.com/Why-do-Afro-centrists-claim-that-the-first-samurai-warrior-was-a-black-African
"For aSamurai to bebrave, he must have abit of blackblood "
日本人ならそんなことわざないこと誰でも知ってると思うんですけど、当然アサクリ関係ないサイトで見ることになる
リンク貼れないけど下記とか
https://www.levelman.com/where-black-people-fx-shogun/
あとアサクリ関係なくYASUKEの名前もトンデモ記述の中で見るけど、悪気無さそうなサイトや個人サイト貼るのはやめとくね
アフロ侍かっこいいし、肌の色の濃いヒーローやヒロインが活躍する作品はもっと増えるべきだと思う
あと、おそらく、日本にアフリカ系の血を引いた人が居たか居なかったかなら居た可能性もあるのではないかと思う
だから、肌の色の濃いヒーローが主人公なのはぜんぜん有りだと思うけど、
とにかく下記みたいな発言をやめろと、日本の団体や文化財の『使用許可ガン無視』と『利用料金ガン無視』の無断利用はやめろに尽きますわ
Assassin'sCreeddirector: The righttime totake series toJapan |BBC
https://www.bbc.com/news/articles/c163jexl7rxo
Shadow’s trailer also generated backlash from somegamers,who criticised the choice of Yasukeas amain characterover a nativeJapanese protagonist.
Opponents have accused those critics ofbeing racist, and have pointedout that Yasukeis basedon a real-life person.
Charles, speaking to Newsbeat before the trailer dropped, says the developers “put a lot of emphasison authenticity and making sure we depictJapan and the culture right”.
“So when westarted the project, we had a historian with us from dayone,” he says.
He says theteam also consulted weapons experts and travelled toJapan toget afeel for the landscape and locations inthe game.
シャドウのトレーラーは、一部のゲーマーからの反発も生みました。彼らは、日本人主人公ではなく弥助を主人公として選んだことを批判しました。
これに対して、批判者たちを人種差別主義者だと非難する声も上がっており、弥助が実在の人物に基づいていることが指摘されています。
チャールズは、トレーラー公開前にNewsbeat(BBCのニュース番組)との対話で、開発者たちが「日本とその文化を正しく描写することに重点を置き、真正性を重視した」と述べています。
あと首云々もひでーわな
Itwas surprisingly gory,like the decapitations,you couldget coated inblood. How vitalis that to theassassin’sfantasy?
(斬首シーンなどでは、予想外に残虐で、血まみれになることもありますね。これはアサシンのファンタジーにとってどれほど重要なのでしょうか?)
Ithink it’s not anassassin thing,it’s aJapan thing in ourcase. So lookingatdeathwas a day-to-day occurrence in that period, and the waymost people died inJapan during thattimeisclean decapitations.
So we didn’t want toshyaway fromit, althoughyou can turn off theviolence ifyou want. There’s options forit.You can turn off theblood,you can turn off the dismemberment and stuff. Soit’smore trying to be faithful to thewaraspect ofJapanat that period.Deathwas acommon thing and decapitationwas not a strange sight inJapan.
私たちの場合、これはアサシンに関することというよりも、日本に関することだと考えています。当時の日本では、死を目にすることは日常的なことでした。そしてその時代の日本で多くの人々が死んでいった方法は、きれいな斬首でした。
ですので、私たちはそれを避けようとはしませんでした。ただし、望めば暴力表現をオフにすることもできます。そのためのオプションがあります。血の表現をオフにしたり、切断などの表現をオフにしたりすることができます。これは、むしろその時代の日本の戦争の側面に忠実であろうとする試みなのです。死は日常的なことであり、斬首は日本では珍しい光景ではありませんでした。
https://videogames.si.com/features/assassins-creed-shadows-interview
公開済であるコンセプトアート2点に、関ケ原古戦場おもてなし連合「関ケ原鉄砲隊」の旗が無断で使用されているとのご指摘を受けております。
当該アートはコレクターズエディション内のアートブックに収録されることを除き、以降は新たな使用・配布等は行われません。
↓ でも実際には削除してません (なぜか、UBI許せないマンがUBIに抗議しろと町や観光協会にアタックしてくるみたいなのでアカウント名は省略)
私の書き方が悪かったかもしれないので再度返信についてポストします
・指摘のあった画像(吊るし首の方)は削除されました
・背景に小さく映り込んでいる画像は印刷の関係で判別できないため収録されています
箇条書きですが上記3点が回答でした
anond:20240723220838anond:20240724015401