Labor issues in academia….

The issue with low pay and no benefits for adjunct professors has been around for a while now. Here is a new take on it from Slate Magazine looking at the oft used phrase “do what you love”. Money quote:

If DWYL denigrates or makes dangerously invisible vast swaths of labor that allow many of us to live in comfort and to do what we love, it has also caused great damage to the professions it portends to celebrate. Nowhere has the DWYL mantra been more devastating to its adherents than in academia. The average Ph.D. student of the mid-2000s forwent the easy money of finance and law (now slightly less easy) to live on a meager stipend in order to pursue his passion for Norse mythology or the history of Afro-Cuban music.
The reward for answering this higher calling is an academic employment marketplace in which about 41 percent of American faculty are adjunct professors—contract instructors who usually receive low pay, no benefits, no office, no job security, and no long-term stake in the schools where they work.

The problem is how to fix. Adjuncts are typically hired to teach sections filled with students but no available tenure-line instructional faculty member. This happens when faculty members are on sabbatical, or when they “buy out” of their course load from research grants (remember at US research universities, a faculty member typically splits their work between research, teaching and service). In theory the “buy down” from the grant should be sufficient for a living wage for the adjunct but as a matter of fact, rarely is that functionally the case (i.e. the adjunct is paid much less than the amount of the buy down).

Why?

Because the buy-down dollars are just too tempting for budgeteers….and because the market supports the low wages paid. With the advent of adjunct unionization, this may perhaps change.

Where are our readers?

Google Analytics “blue map” of Advanced Studies last 24 months

To answer the question: you are apparently all over the globe with a not unexpected majority of hits here in the United States.

We’ll continue to work to attract new readers in Madagascar and Papua New Guinea..among other places.

In the meantime, thank you for your readership and we’ll try to keep the focus appropriately global for our discussions.

Good news for US science R&D…

The report is from the NSF. ScienceInsider story, here. Overall I see this as a very positive trend. Academia will catch up as federal R&D investments grow–its a lagging indicator. On the business side, I see research partnerships between academia and industry as being ever more important. Those partnerships are currently at the center of our focus here at Krasnow and I think that emphasis will extend across academia.

All of this depends on some modicum of political stability as far Congress is concerned. But I think we have reason to be cautiously optimistic.

Oxford’s Robin Dunbar thinks TB may have co-evolved with us as a NAD producing symbiont when meat wasn’t available…

The paper is open access and is here. Short version: humans evolved to be meat eaters to handle their big brains’ energy budget. Myobacterium tuberculosis co-evolved to be initially a “hedge” symbiont: when meat wasn’t available (with its abundant NAD fuel for our brains) the microbe was there…

Pretty cool idea.

Poets can be fraudsters too….

Apparently misconduct is not just limited to scientists, watch out for the poets! Story here. Money quote:

In poetry, at least, everyone agrees it’s not about the money. “One of the hardest things is that the stakes in poetry are not very high,” Kocher said. “I’m not a rocket scientist. I’m not going to cure cancer with one of my poems. I don’t get paid an extraordinary amount of money, and I don’t have any great notoriety outside of the writing community. So to take something that most people engage in as an act of joy and sully it this way—it just seems one of the most egregious offenses.”

IBM’s new cognitive computing business unit…

There are a lot of good stories on this. A good summary at The Economist, here. I’m particularly interested in the notion of cognitive computing. On the one hand, Watson looks to me to be a version of strong AI, using conventional high performance computing to drive an expert’s expert system. On the other hand, there are host of folks (including Dharmendra’s group out at IBM Almaden) who are using neurally-inspired architectures with an aim towards a new version of cognitive computing whereby the machine computes in ways that are like the way the human brain does. This latter approach is more interesting to me if only for its incredible efficiency (20 watts of energy in to power a human mind).