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It is hard to say just when the gig economy came to Universities. In the 1970s and early 1980s, at least in a Computer Science Department, the professor1 typically taught and often taught first year students. This was because it was seen as the professor's duty, their responsibility and, incredible as it now seems, there was a wish not to load up the often new, junior staff with tough jobs. In the 1990s career grand total prize-money, that is grants won, became increasingly important as a surrogate measure for "quality" – it seems to be transparent, impartial, judged by your peers, and is certainly easily measured2 – regardless of whether someone's work actually needs a grant or not. Many grant recipients hit on the idea of buying themselves out of teaching which is now often done by one of their postgraduate students or postdocs. Few if any Professors teach. Teaching came to be seen as less important, less prestigious, a view crystallised in the way that University [Rankings]3 are calculated. There have long been some casual staff but now reportedly4 "more than half" of Melbourne University's "17,000" staff are "on casual contracts" and "another quarter are on fixed-term contracts." Didn't it just sneak up on us, in part fuelled by the rich fees from large numbers of overseas students. "'It's like a mining boom,' Glyn Davis5 told [Sylvester4] 'and like all mining booms it comes to an end, so you invest it in things that will matter into the future.' For the University's senior management it is buildings that will matter into the future. 'What you don't do,' Davis added, '[is] load up the institution with expensive permanent staff, because you know that later this will be a significant problem.'"4
Also see wage theft case6,7.
1 British terminology, a Department's academic staff consisted of one or more Professors (often just one in a new Computer Science Department), then senior lecturers, lecturers, and tutors.
2 "Not everything that can be counted counts, and not everything that counts can be counted." Attributed to W. B. Cameron, 'Informal Sociology: A Casual Introduction to Sociological Thinking', 1963, by Quote Investigator.
3 Rankings upon which the KPIs of many a Vice-Chancellor, Deputy Vice-Chancellor (Research), Dean, and Deputy Dean (Research) depend.
4 B. Silvester, 'Divide and Conquer, The Age, p.32, 16 November 2019, SMH [16/11/2019], and 'Rumbling in the (contracted) ranks of Australia's most elite university', The Citizen (a publication of the Centre for Advancing Journalism), [15/11/2019].
5 Glyn Davis, Vice-Chancellor of Melbourne University 2005-2018 (and husband of Margaret Gardner, Vice-Chancellor of Monash University 2014...).
6 "University of Melbourne to repay millions to staff after decade-long underpayment practices. Millions of dollars are being quietly repaid to at least 1,500 academics in a 'wage theft' case ..." ABC [20/7/2020].
7 "University underpayment so rampant tutors 'instructed to do a poor job' ..." ABC [18/8/2020]. Pointed the finger at ten Universities.

The movie '2001' (1968) which starred 'HAL' was set in, err well, 2001. 'Blade Runner' (1982) was set in November 2019. As of that date we are still far from creating lifelike robots (~replicants) or a genuine artificial intelligence although computers have now beaten top human players at Chess (1996) and Go (2015). 'Terminator' (1984) has a cyborg time-travel from 2029 back to the then present. We'll see.

The annual THES University Rankings, by subject, are out. See [rankings]. Of course everyone says that such rankings are a "game" that should not be taken too seriously but rather "played". However, many a KPI, bonus, job, or promotion, . . . , is made or lost according to them.
Goodhart's law (1979): "Any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes."
Campbell's law (1979): "The more any quantitative social indicator is used for social decision-making, the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor."

The longest common subsequence (LCS or LCSS) problem is closely related to the edit distance algorithm and they are used to compare two strings of characters for similarity and, in bioinformatics, for sequence alignment and homology. The 'Bit-String Longest-Common-Subsequence Algorithm' speeds up the dynamic programming algorithm (DPA) for the problem by a factor of the word-length of the computer, typically ×32 or ×64. Added an interactive Javascript [demonstration] of the algorithm.

On Universal Codes for Integers: Wallace Tree, Elias Omega and Variations, Lloyd Allison, Arun Konagurthu & Daniel Schmidt, 1906.05004 at [arXiv], 13 June 2019. The implied probability distribution of a universal code is a reasonable choice when the true distribution of a source is unknown and provided only that the source's messages can be plausibly ordered, {m1, m2, ...}, by decreasing probability – by increasing code-word length (– with ties resolved arbitrarily). There are interactive implementations of the universal codes discussed in the report [here].

'If I didn't have you' is a love song by Tim Minchin to his wife, [www]['19]. It is also an excellent introduction to statistics, bell curves, and the like. On the subject,

'Charlie No 1' (1998) by The Whitlams contains...
Some say love it only comes once in a lifetime
Well once is enough for me
She was one in a million
So there's five more just in New South Wales
I think you will find that five million included both men and women. But Australia is cool with that.
(Tim Minchin's web site is [timminchin.com]['20].)

"... Mathematicians tend to publish at rates that are modest compared to some other sciences. ... Even some of the best young mathematicians publish relatively few papers. A study of the 40 mathematicians winning Sloan Fellowships in 2005-2006 shows that 70% published an average of two or fewer articles per year in the five years preceding their award. Even more senior mathematicians have modest publication rates. Of the 22 mathematicians receiving Guggenheim Fellowships from 2002-2006, half published an average of two or fewer articles per year in the five years preceding their award. These two groups represent an exceptional group of highly recognized mathematicians ..." — AMS [20/9/2015].  Makes you think, but then, "Thousands of scientists publish a paper every five days ..." — see [implausibly prolific].

Small & interesting v. big & boring: "... we analyse more than 65 million papers, patents and software products that span the period 1954-2014, and demonstrate that across this period smaller teams have tended to disrupt science and technology with new ideas and opportunities, whereas larger teams have tended to develop existing ones. Work from larger teams builds on more-recent and popular developments, and attention to their work comes immediately. By contrast, contributions by smaller teams search more deeply into the past, are viewed as disruptive to science and technology and succeed further into the future — if at all. ..." from 'Large teams develop and small teams disrupt science and technology', Wu, Wang & Evans, Nature, Feb. 2019, [doi:10.1038/s41586-019-0941-9].

Inspired by the 1964 World Fair (peace through understanding), science fiction writer Isaac Asimov wrote the essay, Visit to the World's Fair of 2014, NYT [16/8/1964]. In December 1983, to celebrate Orwell's [1984], 'The Star' asked Asimov to predict the world of 2019. See how he did: [www].
In 1964 Arthur C. Clarke, author of 2001 A Space Odyssey, made his own predictions [bbc], many of which look pretty good from the early 21C.

There have been many 'systems biology' papers in the scientific literature claiming the existence of network 'motifs' (patterns, frequent subgraphs) in biological networks such as gene regulatory networks, and protein-protein interaction networks. Among the proposed motifs are the 'feedforward loop' (FFL), 'bifan', 'dense overlapping regulon', 'single input', 'multiple input' units. There are also contrary opinions to some of the conclusions, for example, questioning links between architecture and function [www], and pointing out problems in the definition, counting, and origin, of motifs [www].
Chapter 11, 'Graphs' [doi:10.1007/978-3-319-76433-7_11], of Coding Ockham's Razor examines the problems of discovering graph (network) motifs and of using motifs to compress graphs (biological or otherwise), much in the way that text patterns can be used to compress text files. #bioinformatics Also see the [mmlist].

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