OpenLLM-France/wikimedia huggingface dataset:
# Orienteering/Videos/Map skills

The Presenter stands at the start triangle, staring at her map, while other orienteers (a variety of ages, from juniors to super veterans) run off purposefully toward their first controls [suggest this can be in 2X or 4X speed as the Presenter studies her map with a furrowed brow].
PRESENTER (V/O)
I’ve just started my first orienteering event. Everyone around me seems to know exactly where they’re going, but I haven’t really got a clue. All I know is that I am at this little triangle on the map.
CLOSE UP of map, thumb close to the start triangle. The presenter looks up.
PRESENTER (to camera)
I think I am going to need some help.
She clicks her fingers. The Novice Instructor appears magically in the frame (JUMPT CUT - a la ‘The Goodies’).
INSTRUCTOR
Need some help?
PRESENTER
Thought you’d never ask.
CLOSE UP of the map.
PRESENTER
So what am I actually looking for?
INSTRUCTOR
You’re looking for the feature in the centre of that circle. Which in this case is a track junction [or whatever].
PRESENTER
And that’s my first control?
INSTRUCTOR
Yes.
PRESENTER
And I have to do them in order?
INSTRUCTOR (ad lib, along the lines of…)
In this kind of event, yes. There are other events (eg. Street O, rogaines) where you don’t get the controls in any set order. But today, you need to.
PRESENTER
(CLOSE UP of map)
That’s a shame, because if I just got this one before this one and this one…
INSTRUCTOR
Then you’d be disqualified.
PRESENTER
Ah.
CUT TO footage of elite orienteers running through the forest INTERCUT with SCREEN SHOT of GPS tracking on a map.
PRESENTER (V/O)
An orienteering map is a highly specialized piece of cartography. Working from detailed aerial photographs, orienteering map makers spend hours doing fieldwork that involves marking on tiny details – such individual boulders and creek beds - that orienteers use to navigate through the terrain.
Back to Presenter and Instructor.
PRESENTER
So how do I know what these symbols on the map represent in the forest?
INSTRUCTOR (ad-lib…)
Each map has a legend [CLOSE UP] that shows you what each symbol on the map means. The more you orienteer, the more you learn to recognize what each symbol represents in the forest.
PRESENTER
And what about these brown squiggly lines?
INSTRUCTOR
Those are contours.
PRESENTER
Which means I’m going up or down, right?
INSTRUCTOR
Usually up.
INSTRUCTOR
(laughs)
Right.
Over ad-lib chit chat, where Instructor points at things on the map, then at features in the terrain (no sound) –
PRESENTER (V/O)
So now I know where I have to get to and what I’m looking for when I get there. The next question is – which direction do I go in?
# Orienteering

Orienteering is a family of sports that requires navigational skills using a map and compass to navigate from point to point in diverse and usually unfamiliar terrain, and normally moving at speed. Participants are given a topographical map, usually a specially prepared orienteering map, which they use to find control points. Originally a training exercise in land navigation for military officers, orienteering has developed many variations. Among these, the oldest and the most popular is foot orienteering. For the purposes of this article, foot orienteering serves as a point of departure for discussion of all other variations, but basically any sport that involves racing against a clock and requires navigation using a map is a type of orienteering.
Orienteering is included in the programs of world sporting events including the World Games (see Orienteering at the World Games) and World Police and Fire Games.

## Projects

* Videos
# Orienteering/Videos/Arriving

The Presenter opens up the boot of her car and pulls out a pair of trail running shoes. She is already wearing shorts (or track pants) and a sporty t-shirt and/or jacket. Sitting on the edge of the boot, she proceeds to take off her casual shoes and pull on the trail running shoes.
PRESENTER (to camera)
I’m here at my very first orienteering event. I’ve got my map, my compass, my control description, my timing chip and the special control card which I’ll need to take on my orienteering course today.
Close-up of map, compass and card in a pile next to the presenter.
PRESENTER (to camera)
In an orienteering race, the aim is to get through the checkpoints – called ‘controls’ – as quickly as possible. And for a lot of people, that means running. I’m not sure how much running I’ll be doing today - that will depend on just how difficult my course is.
CUT TO the presenter chatting to an official (novice instructor) at the registration table [perhaps with a ‘Need help? Ask me’ or ‘Helper’ sticker or t-shirt].
PRESENTER
So just how hard are these courses?
INSTRUCTOR (ad-lib along the lines of…)
Well, the ones with the lowest numbers are very tricky, and they’re usually the longest too. As you go down through the numbers, the courses get shorter but not necessarily easier. At every competition there are also courses with moderate navigation for people with some experience and courses with very easy navigation for beginners.
PRESENTER
So what course would you suggest that I do?
INSTRUCTOR
I’d suggest you do the easy navigation. Course 8 [or whatever].
The Instructor hands over the correct registration card.
PRESENTER
How far is that?
INSTRUCTOR
About two kilometers.
PRESENTER
And how long will that take me?
INSTRUCTOR
(laughs)
We’ll just have to wait and see.
PRESENTER
So I just fill in this card now?
INSTRUCTOR
That’s right. Put your name here, course here…[etc.]
The Presenter leans on the table and starts filling in the details. Close up of registration card, filling in the correct course no. etc. The Presenter looks up as She gets to the ‘Car Registration’ part.
PRESENTER (V/O)
Car registration? Is that in case I get a parking ticket?
INSTRUCTOR (ad lib…)
No, it’s so we can see if you’re still here at the end of the day. Sometimes people forget to hand in their control card after they’ve finished their course, and we need to know if we should send out a search party.
PRESENTER
That sounds a bit ominous. Should I take my GPS?
INSTRUCTOR
Actually, that’s not allowed.
PRESENTER
No GPS?
INSTRUCTOR
Not a GPS that gives you your position, no. Just your map and your compass.
PRESENTER
And my superior sense of direction.
INSTRUCTOR
(laughs)
Any more questions?
PRESENTER
Just one. Which way to the start?
Silently, the Instructor points to a large, un-missable START sign and arrow, pointing along a track.
PRESENTER
Ah.
She starts to jog off in that direction.
# Wikiversity Law Reports/Sweeney v Boylan Nominees

TL;DR: a refrigerator lessor is not vicariously liable for negligence committed by a person engaged to repair a refrigerator, where that person was an independent contractor rather than an employee of the refrigerator lessor

## Facts

* The defendant operated a business of leasing refrigerators to petrol stations. The defendant was responsible for maintaining the refrigerator.
* The plaintiff customer went into a petrol station to buy milk and opened such a refrigerator. The refrigerator door had been repaired badly by a mechanic hired by the defendant, and as a result the door fell off and caused injury to the appellant.
* The plaintiff customer was unsuccessful in suing the petrol station operator. The plaintiff customer did not sue the mechanic.
* The plaintiff customer sued the refrigerator lessor and was successful at first instance, but this judgment was overturned by the Court of Appeal of New South Wales. The plaintiff customer appealed to the High Court.

## Held

* Rejected the proposition that 'if A "represents" B, B is vicariously liable for the conduct of A': paragraph 26.
* While it is possible for a principal to be liable for the acts of an independent contractor in some circumstances, the general principle that a principal is vicariously liable for the negligence of its employees but not of independent contractors is firmly entrenched in the law: paragraph 33.
* The refrigerator lessor was not liable for the injuries caused by the faulty refrigerator door.

## Important parts of the judgment

* Paragraph 11ff discusses the legal and policy basis of the modern doctrine of vicarious liability.
* Paragraph 16ff discusses the meaning of the terms 'agent' and 'representative' as they are used in relevant case law.
* Kirby J dissented on the basis that, while the mechanic was not an employee of the refrigerator lessor, the refrigerator lessor was vicariously liable for the mechanic's negligence because the mechanic was a 'representative agent' of the refrigerator lessor (the 'special principle' in Colonial Mutual Life Assurance Society Ltd v Producers and Citizens Co-operative Assurance Co of Australia Ltd [1931] HCA 53; (1931) 46 CLR 41): see in particular paragraphs 85 and 113.

## Other publishers' references

* [2006] HCA 19
* (2006) 226 CLR 161
* (2006) 227 ALR 46
* (2006) 80 ALJR 900
# Wikiversity Law Reports/Take Harvest Ltd v George H Liu

TL;DR: A parol agreement, unenforceable under the Statute of Frauds, cannot be used as a defence. However, equitable rights may arise from the surrounding facts; in this case, remitted to trial court to determine equitable rights.

## Other publishers' references

* [1993] AC 552
# Wikiversity Node Cambridge/Introduction
## How to join the session

Go Here

## Wikimedia Projects
### Wikipedia - Wikiversity - Commons - Data - Source

Some of the interlinked wikis:

### Wikipedia

Wiki + Encyclopedia?
Encyclopedias and decolonising knowledge
Daniel Murray (1852-1925) pioneered the use an encyclopedia to as an educational resource to combat racism and create an independent Africana curriculum in the nineteenth century. He worked with W. E. B. Du Bois and Thomas J. Calloway in creating The Exhibit of American Negroes at the 1900 Paris Exposition.
External link: W.E.B. Du Bois and the Making of the Encyclopedia Africana, 1909-1963 by Henry Louis Gates

### Wikimedia Commons

"Wikimedia Commons is a media file repository making available public domain and freely licensed educational media content (images, sound and video clips) to everyone, in their own language. It acts as a common repository for the various projects of the Wikimedia Foundation, but you do not need to belong to one of those projects to use media hosted here. The repository is created and maintained not by paid archivists, but by volunteers. The scope of Commons is set out on the project scope pages." From: Commons:Welcome

### Wikiversity

Wikiversity is another linked Wikimedia project: "Wikiversity is for learning. It is a place where you'll find free learning materials and learning projects. Everyone can participate. There is no cost, no advertising, and no credentials are required. No degrees are awarded — just learning." It uses the same Mediawiki Mark up Code, but with different community goals, forms of self-organisation.

### Other Wikimedia projects

* Wikisource – Wikisource:Community portal: an online library of free-content texts.
* Wikidata – Wikidata Main Page: a free and open knowledge base that can be read and edited by both humans and machines.
* Wikibooks – Wikibooks:Welcome: a Wikimedia project for collaboratively writing open-content textbooks that anyone, including you, can edit right now by clicking on the edit link that appears near the top of each Wikibooks page.

## Practice

Wikiversity
* open account
* set up user page on wikiversity
* leave a comment on this page's talk page (click on discuss , above)
* leave comments on user talk pages

## Overview

Introduce Portal:Decolonise Knowledge
Student campaigns - RMF, Goldsmiths etc
Research - reading lists, art, science etc
Intersections: intersection with Free education

## Practice

* set up a page for the campaign - they need to decide where that goes

### Wikimedia Commons

* set up user page on commons
* uploading to commons
# Wikiversity Law Reports/Waltons Stores v Maher

TL;DR: Promissory estoppel provides a cause of action, not just a defence, i.e. it is a sword as well as a shield. Promissory estoppel can arise in the absence of pre-existing contractual rights.

## Facts

* M, the owner of land with a building on it, was negotiating with W, a retailer, for W to lease the land. If the lease was to go ahead, M would need to demolish the existing building and build a new building suited to W's needs. M and W were negotiating the terms of the proposed lease.
* W led M to believe that the current draft lease was acceptable to it.
* Unknown to M, W had decided not to execute the lease yet so as to keep its options open.
* M began to demolish the existing building and began to build the new building.
* W told M that it no longer wished to enter into the lease.

## Held

* Having led M into the erroneous assumption that W intended to execute the lease, W was estopped from denying it was bound by its implied promise to execute the lease.

## Other publishers' references

* [1988] HCA 7
* (1988) 164 CLR 387
# Wikiversity Law Reports/Pirie v Saunders

TL;DR: A file note made by one party to negotiations for a lease, listing the terms agreed so far, does not satisfy the Statute of Frauds.

## Facts

* A landlord and a (would-be) tenant entered negotiations to let out a shop.
* A formal lease agreement was at least partially prepared by one party but not executed.
* The Conveyancing Act 1919-1954 (NSW), s 54A (NSW Statute of Frauds) required signed writing for a lease to be binding.
* The tenant obtained a copy of a file note made by the landlord's solicitor recording the landlord's instructions in relation to the preparation of the formal lease agreement. The note recorded the terms agreed so far but also noted that other terms remained outstanding.
* The tenant sought to compel the landlord to perform the lease, trying to use the file note to satisfy the Statute of Frauds.

## Held

* The note recorded the state of incomplete negotiations, not a finished agreement.
* The note was not signed by the landlord. The 'authenticated signature fiction' was discussed but not applicable to the facts.
* Therefore the tenant could not enforce the lease.

## Other publishers' references

* [1961] HCA 4
* (1961) 104 CLR 149
* Networked Knowledge Contract Law Casenote: Pirie v Saunders
# Wikiversity Law Reports/Sentenza Corte Costituzionale n. 120/2014 (Insindacabilità Interna Corporis Acta)

* Sentenza Corte Costituzionale n. 120/2014
* (Insindacabilità Interna Corporis Acta)
* Summary
* Cases of autodichia cannot be brought before a Court by means of a judicial review.
* Court
* Constitutional Court of Italy
* Background
* An employee of the Senate appealed to the Court of Cassation, pursuant to art. 111 of the Constitution, against a regulation of Parliament, in particular of the Senate guarantee council, in the context of a judgment of compliance relating to a work case. The Court of Cassation raised a question of constitutional legitimacy of art. 12 of the Rule of the Senate, where it attributes to the Senate the power to judge exclusively and definitively appeals against the acts and measures adopted by the administration of that branch of Parliament against their employees.
* Held
* The Court reiterates, as in its previous judgment no.154/1985, that parliamentary regulations and Parliamentary acts (Interna corporis acta) cannot be reviewed, because they are not included in the acts subject to judicial review pursuant to art. 134 of the Constitution, but they are a constitutional source in itself, to implement the particular autonomy of Constitutional organs.
* So the exercise of judicial powers by domestic authority (without using external courts), in Italian Constitutional organs, continues.
* Notes
* (2014) Const. Court, n. 120 (est. Giuliano Amato)
# Wikiversity Law Reports/Yanner v Eaton

TL;DR: 'Property' is shorthand for a bundle of rights; which rights are meant will depend on the purpose of the statute; vesting certain 'property' rights over X in 'B' does not extinguish other rights over X held by 'A'.

## Facts

* Y, an Aboriginal person, caught a wild crocodile without obtaining a permit.
* E charged Y with the offence of taking fauna without a permit.
* The Fauna Conservation Act 1974 (Qld) provided that all wild animals were 'property' of the Crown.
* The Native Title Act 1993 (Cth) provided that State law could not prevent an Aboriginal person from exercising their native title right to hunt &c.

## Held

* The Fauna Conservation Act 1974 vested some rights in the Crown but did not extinguish the native title rights and interests in fauna. Therefore, at the time the Native Title Act 1993, there continued to be a native title right to hunt &c which the Native Title Act preserved from that time onwards.
* Therefore Queensland law could not prohibit Y from catching the crocodile and he had not committed an offence.

## Other publishers' references

* [1999] HCA 53
* (1999) 201 CLR 351
# Reinforcement Learning/Statistical estimators: Bias and Variance
## Statistical estimator

In statistics, an estimator is a rule for calculating an estimate of a given quantity based on observed data.
Suppose we have a statistical model, parameterized by a real number θ, giving rise to a probability distribution for observed data, $P_{\theta }(x)=P(x\mid \theta )$.
Assume statistic ${\hat {\theta }}$ serves as an estimator of θ based on any observed data $x$. That is, we assume that our data follow some distribution $P(x\mid \theta )$ with unknown value of θ (in other words, θ is a fixed constant that is part of this distribution, but is unknown). We construct some estimator ${\hat {\theta }}$ that maps observed data to values that we hope are close to θ.

## Bias

The bias of an estimator ${\hat {\theta }}$ relative to $\theta$ is defined as
    $\operatorname {Bias} _{\theta }[\,{\hat {\theta }}\,]=\operatorname {E} _{x\mid \theta }[\,{\hat {\theta }}\,]-\theta$
where $\operatorname {E} _{x\mid \theta }$ denotes expected value over the distribution $P(x\mid \theta )$, i.e. averaging over all possible observations $x$.
The meaning of a biased estimator is that there is a systematic difference between the estimated parameter (${\hat {\theta }}$) and the real value of the parameter ($\theta$). However, usually the difference becomes smaller with growing number of input data and eventually a biased estimator becomes useful.
An estimator is said to be unbiased if its bias is equal to zero for all values of parameter θ.

# Variance

The meaning of an estimator with high variance is that the estimated parameter (${\hat {\theta }}$) is very sensitive to the input (observed data, $x$)
The variance of an estimator ${\hat {\theta }}$ is${\text{Var}}({\hat {\theta }})=\mathbb {E} _{x|\theta }{\big({\hat {\theta }}-\mathbb {E} [{\hat {\theta }}])^{2}{\big ]}$

## Mean squared error

The mean squared error (MSE) of an estimator ${\hat {\theta }}$ is${\textrm {MSE}}({\hat {\theta }})={\textrm {Var}}({\hat {\theta }})+{\textrm {Bias}}_{\theta }({\hat {\theta }})^{2}$
# Regular ring/Positive characteristic/Forcing algebra/Not inside/Local cohomology/Fact/Proof

This follows from fact and $f\notin I^{*}$.
# Regular ring/Positive characteristic/Tight closure trivial/Fact/Proof

We assume $d\geq 2$, lower dimensions may be treated directly. Because of $I^{*}\subseteq \bigcap _{n\in \mathbb {N} }(I+{\mathfrak {m}}^{n})^{*}$, we can also reduce to the case of a primary ideal $I$. Suppose that $f\notin I$, and let $c_{d-1}\in H^{d-1}(D({\mathfrak {m}}),{\mathcal {O}}_{U})^{\beta _{d}}=H_{\mathfrak {m}}^{d}(R)^{\beta _{d}}$ be the corresponding non-zero class arising from a finite free resolution. At least one component, say $c'\in H_{\mathfrak {m}}^{d}(R)$, is then also non-zero, and we can write it in terms of Čech-cohomology as
    $c'={\frac {h}{x_{1}^{n_{1}}\cdots x_{d}^{n_{d}}}}\,,$
where $x_{1},\ldots ,x_{n}$ is a regular system of parameters of $R$ and $n_{j}\geq 1$. We have to show that there is no $z\neq 0$ such that $zF^{e*}(c)=0$ for all $e\in \mathbb {N}$. Multiplying the class with some element of $R$ we may assume that $h$ is a unit. We have (with $q=p^{e}$)
    $F^{e*}(c')={\frac {h^{q}}{x_{1}^{qn_{1}}\cdots x_{d}^{qn_{d}}}}\,$
and its annihilator is ${\left(x_{1}^{qn_{1}},\ldots ,x_{d}^{qn_{d}}\right)}$. But then
    $\bigcap _{e\in \mathbb {N} }{\left(x_{1}^{qn_{1}},\ldots ,x_{d}^{qn_{d}}\right)}\subseteq \bigcap _{e\in \mathbb {N} }{\left(x_{1}^{n_{1}},\ldots ,x_{d}^{n_{d}}\right)}^{q}=0\,.$
# Reinforcement Learning/Temporal Difference Learning

Temporal difference (TD) learning is a central and novel idea in reinforcement learning.
* It is a combination of Monte Carlo and dynamic programing methods
* It is a Model-free learning algorithm
* It both bootstraps (builds on top of previous best estimate) and samples
* It can an be used for both episodic or infinite-horizon (non-episodic) domains
* Immediately updates estimate of V after each $(s,a,r,s')$
* Requires the system to be Markovian
* Biased estimator of value function but often much lower variance than Monte Carlo estimator
* Converges to true value in finite state cases, but does not always converge with infinite number of states (known as function approximation)

## Algorithm Temporal Difference Learning TD(0)

TD learning can be applied as a spectrum between pure Monte Carlo and dynamic programing, but the simplest TD learning is as follows
* Input: $\alpha$
* Initialize $V^{\pi }(s)=0,\forall s\in S$
* Loop
** Sample tuple $(s_{t},a_{t},r_{t},s_{t+1})$
** Update $V^{\pi }(s_{t})$$V^{\pi }(s)=V^{\pi }(s)+\alpha {\big\underbrace {[r_{t}+\gamma V^{\pi }(s_{t+1})]} _{\text{TD target}}-V^{\pi }(s){\big )}$
Temporal difference error is defined as$\delta _{t}=r_{t}+\gamma V^{\pi }(s_{t+1})-V^{\pi }(s_{t})$

## n-step Return

$n=0:$ $G^{(0)}={R_{t}+\gamma V(s_{t+1})}$ is TD(0)
$n=1:$ $G^{(1)}={R_{t}+\gamma R_{t+1}+\gamma ^{2}V(s_{t+1})}$
and so on up to infinity
$n=\infty :$ $G^{(\infty )}={R_{t}+\gamma R_{t+1}+...+\gamma ^{T-1}V(s_{t+T-1})}$ is MC
Is defined as n-step learning TD(n)
$V^{\pi }(s)=V^{\pi }(s)+\alpha {\bigG^{(n)}-V^{\pi }(s_{t+1})]{\big )}$
# Reinforcement Learning/Policy iteration

Policy Iteration (PI) is one of the algorithms for finding the optimal policy (MDP control).
Policy iteration is a model-based algorithm.
The complexity of the algorithm is $|A|\times |S|\times k$ where $k$ is the number of iterations needed for convergence. Theoretically, the maximum number of iterations is $|A|^{|S|}$.
The algorithm converges to the global optimum.

## State-action value Q

State-action value of a policy $\pi$, is calculated by taking the specified action $a$ immediately, then following the policy$Q^{\pi }(s,a)=R(s,a)+\gamma \sum _{s'\in S}P(s'\mid s,a)V^{\pi }(s')$Here, $R(s,a)$ is the reward function in MDP and $P(s'|s,a)$ is the transition model.

## Algorithm

* Set $i=0$
* Initialize $\pi _{0}(s)$ randomly for all states $s$
* While $i=0$ or $|\pi _{i}-\pi _{i-1}|_{1}>0$ (L1-norm, measures if the policy changed for any state):
** Compute state-action value of a policy $\pi _{i}$, for all $s\in S$ and all $a\in A$ $Q^{\pi }(s,a)=R(s,a)+\gamma \sum _{s'\in S}P(s'\mid s,a)V^{\pi }(s')$
** Compute new policy $\pi _{i+1}$, for all $s\in S$ by choosing the action that returns the maximum state-action value for each specific state$\pi _{i+1}(s)=\arg \max _{a}Q^{\pi _{i}}(s,a)~~~\forall s\in S$

## Explanation

In each iteration, by definition we have$\arg \max _{a}Q^{\pi _{i}}(s,a)\geq Q^{\pi _{i}}(s,\pi _{i}(s))=V^{\pi _{i}}(s)~~~\forall s\in S$

## Proof

${\begin{aligned}V^{\pi _{i}}(s)\leq &~\max _{a}Q^{\pi _{i}}(s,a)\\=&~\max _{a}R(s,a)+\gamma \sum _{s'\in S}P(s'|s,a)V^{\pi _{i}}(s')\\=&~\max _{a}R(s,\pi _{i+1}(s))+\gamma \sum _{s'\in S}P(s'|s,\pi _{i+1}(s))V^{\pi _{i}}(s')~~~\leftarrow {\text{by definition the action with the maximum Q value is taken as the new policy}}\\\leq &~\max _{a}R(s,\pi _{i+1}(s))+\gamma \sum _{s'\in S}P(s'|s,\pi _{i+1}(s)){\Big\max _{a'}Q^{\pi _{i}}(s',a'){\Big ]}\\=&~\max _{a}R(s,\pi _{i+1}(s))+\gamma \sum _{s'\in S}P(s'|s,\pi _{i+1}(s)){\BiggR(s',\pi _{i+1}(s'))+\gamma \sum _{s''\in S}P(s''|s',\pi _{i+1}(s'))V^{\pi _{i}}(s''){\Bigg ]}\\\vdots &\\\leq &~V^{\pi _{i+1}}\end{aligned}}$