Category Archives: Unpublished

Paper Submitted To Alife XV

I’m happy to report that I’ve recently submitted a first paper on the postdoc simulation I’ve been plugging on these pages for some time.  I’ve been working in collaboration with Nic Geard of the University of Melbourne and Ian Wood, my officemate at Teesside.

The submitted paper is titled Job Insecurity in Academic Research Employment: An Agent-Based Model.  Here’s the abstract:

This paper presents an agent-based model of fixed-term academic employment in a competitive research funding environment.  The goal of the model is to investigate the effects of job insecurity on research productivity.  Agents may be either established academics who may apply for grants, or postdoctoral researchers who are unable to apply for grants and experience hardship when reaching the end of their fixed-term contracts.  Results show that in general adding fixed-term postdocs to the system produces less total research output than adding half as many permanent academics.  An in-depth sensitivity analysis is performed across postdoc scenarios, and indicates that promoting more postdocs into permanent positions produces significant increases in research output.

The paper outlines our methodology for the model and analyses a number of different sets of scenarios.  Alongside the comparison to permanent academic hires mentioned above, we also look closely at unique aspects of the postdoc life cycle, such as the difficult transition into permanent employment and the stress induced by an impending redundancy.  For the sensitivity analysis we used a Gaussian process emulator, which allows us to gain some insight into the effects of some key model parameters.

The paper will be under review for the Alife XV conference very shortly, so I don’t want to pre-empt the conference by posting the full text here.  If — fingers crossed — it gets accepted, I’ll post a PDF as soon as it’s appropriate.  If you want a preview or are interested in collaborating on future versions of the model, please get in touch!

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Science About Science: More Scenarios

Since my last post I’ve been doing a lot of work on cleaning up the simulation and adding some additional scenarios to the mix.  After some in-depth discussion with colleague Nic Geard, co-author of the 2010 academic funding model that inspired this work, we decided that a good starting point for this would be to compare a more basic growing population of permanent academics with a population that includes insecure postdocs.

So that led to me getting to work on re-working some things to allow for four possible scenarios:

  1. Core academic funding model as written by Nic and Jason
  2. Simple growing population of permanent academics
  3. Population which includes postdocs, in which research quality does not increase the chances of promotion for postdocs
  4. Population which includes postdocs, in which research quality does increase the chances of promotion for postdocs

This last scenario in particular is intended to investigate how things proceed if we have an optimistic view — we know exactly how good each postdoc is, and we hire only the very best 15% of the current crop during each iteration.  Those in favour of the current structure would most likely argue that competition for limited jobs allows the cream to rise to the top, so we need to investigate whether that assumption holds.

So for the purposes of this post, I’ve done a quick run of the sim for each of these scenarios.  Note that the previous model by Nic and Jason investigates the time-management aspect of grant applications much more deeply — right now I’m just focusing on the mean research output for different groups of academics under each scenario.

Scenario 1: Core Academic Funding Model

If you alter the parameter settings of my version of this model and turn off all my additions — growing populations, promotion mechanisms, and the postdoc system — you end up with a scenario that’s nearly identical to the original model by Nic and Jason.  The only major difference is that in my version the bonus in research quality given to grant-holders is 1.5 rather than 1.25.

So what we see is that grant-holders, as you might expect, have a massive advantage in terms of research productivity:r_mean

Grant-holders are sitting pretty at the top there, although their output fluctuates given that various researchers of differing levels of research talent are jumping in and out of the grant-holders club each semester.

(NB: I’m aware that the non-grant holders are invisible in this graph and the next — I’m working on it.  This is all a work-in-progress, it’ll get there in the end!)

Scenario 2: Growing Population

In the second scenario, I’ve added a mechanism which adds a few academics to the population each semester.  Their research quality and initial level of time investment into grant proposals is randomised.  As in the last post we’re living in a generous society here where research funding stays in step with the growing academic population — 30% of applicants are always funded, regardless of the population size.

Perhaps unsurprisingly, the results look nearly the same as in Scenario 1:

r_mean

Just like in Scenario 1, grant-holders do far, far better than the overall population, particularly those applicants whose grant applications have failed.

Scenario 3: Postdocs, Random Promotions

So now things start getting more bizarre.  In this scenario we introduce the postdoctoral system outlined in my previous posts.  Postdocs are added in proportion to the number of grants that have been funded in a given semester, with a bit of random variation to spice things up.  New postdocs are assigned contract lengths between 4 and 10 semesters.  For the first two semesters their research quality is lower to account for their adjustment period into a new post; similarly, their last two semesters also see a drop in quality due to the time they must devote to finding a new post.

At the end of their contract, postdocs have a 15% chance of being promoted into a permanent position.  That may sound harsh, but that’s actually slightly more generous than reality (the figures I’ve seen have it pegged at 12%).  Research track record doesn’t count in this scenario — this is a world where promotions are entirely a lucky coincidence (some would argue that this is broadly reflective of reality).  Once promoted, they’re now permanent academics and can apply for grants.

So here’s a sample run of the latest formulation of this scenario:

r_mean_pdr

Much like the last set of early results, we see a drastic drop in mean research output amongst permanent academics who are grant-holders, and postdocs don’t do very well in terms of productivity despite allocating 100% of their time to research.  Overall we see no benefit to research output of the population with the introduction of postdocs, and both permanent academics and postdocs see significant variability in their research output.  My interpretation is that the introduction of a randomised population of insecure researchers is massively disruptive — each semester we don’t know how good our postdocs will be, so their output is highly variable, and we also don’t know how good our promoted academics will be, so again we see fluctuations at that level too.

Scenario 4: Postdocs, Non-Random Promotions

This scenario is particularly intriguing to me.  Nic and I had wondered whether selecting only the very best postdocs from the crop for promotion each semester would improve the picture or not.  After all if we pick the best of the best and put them in a position to get grants and thus that juicy grant-holder output bonus, surely things will go much better for our virtual scientists?

Well… not massively:

r_mean_pdr

Now you’ll see in this run that actually both the grant-holders and postdocs appear to be doing a bit better in terms of research output.  Initially this seems good, but by the end of the simulation we see that the mean research productivity for the overall population is actually slightly lower than in the random promotions case!

At first blush this seems nonsensical, but if we ponder it for a moment I think it makes sense.  While the non-random promotions do mean that we get the best of the postdoc population promoted each semester, it still means we’re highly dependent on the whims of the random-number generator — if we get a few bad crops of postdocs, in other words, we just end up with more crappy academics, and our exacting knowledge of postdoc research quality hasn’t saved us from the disruptive influence of the constant influx of new people with highly variable research output and contract lengths.

Moreover, there’s no mechanism at present for postdocs to be mentored or to mature in their research abilities — once crappy, always crappy, in other words.  In real life people may argue that the trials and tribulations of postdoc life can allow young researchers to grow into more productive academics — so that’s another aspect we need to examine.

I’ve done a bunch more runs with different random seeds and seen variations in the output that seem to support these ideas, but I’m going to spare you the 18 other graphs.  Suffice to say that the graph above seems to indicate a lucky series of postdoc recruitment drives more than anything else.  Instead I’ll keep working at it and post more when I’m more clear on my interpretations of this scenario.

SURPRISE NEW SCENARIO: Non-Random Postdoc Promotions, With Mentoring Bonus!

Wow, what a day for you lucky people!  I’ve just decided to do a quick-and-dirty scenario where we give promoted postdocs in the non-random scenario a bonus to their research quality to attempt to simulate postdocs being mentored toward success by their superiors.  Surely we’ll see a change in the fortunes of our virtual scientists now?

Well… not really:

r_mean_pdr

In fact things look almost identical, with the exception of the overall mean research output hitting a plateau rather than dropping slightly at toward the end of the sim, as we saw above.

To be fair, however, the ‘mentoring bonus’ I gave out here was not outrageously large — effectively the promoted, mentored postdocs get a 25% bonus to research quality.  What if I double that to 50%, what do we get?

r_mean_pdr

Ah-ha!  At last, a very slight positive outcome.  Mean research output overall trends ever so slightly upward over the course of this simulation run, rather than plateauing or starting to fall as above.

But I think we’d have to admit here that this is a fairly minimal outcome considering a rather generous scenario — and it’s quite likely this won’t hold in every run and some other runs may show worse results depending on the feelings of the random-number generator.  It seems reasonably consistent at a quick glance — out of 10 runs I’ve just done for this scenario, 7 out of the 10 showed a similar tiny, tiny positive trend.

So what I’ve gathered from today’s work is that increasing the average research output of academics in a postdoc scenario requires some major work: we need to recruit only the very best postdocs; and we need to ensure they get mentoring of high enough quality that they are a full 50% better than they were during their postdoc days.  Even with these powerful tools, that’s still barely enough to overcome the disruptive impact of a fluctuating population of insecure overstressed young researchers.

In real life of course, we don’t have such a transparent method of evaluating research outputs and determining the best postdocs to hire — nor do we have a population of super-mentors who can massively improve the productivity of every single postdoc.  So, if we believe the underlying assumptions of this model, then perhaps we should start to think about whether insecure research posts are a good thing for science or not.

Of course there’s a human dimension here as well — over the many runs I’ve done with the postdoc mechanism running, most simulations top out around 500 active academics at the end of the simulation, and between 5-600 total postdocs hired over the 100 semesters.  Out of those we’ll see between 70-90 postdocs get promoted, while the rest all get the sack and leave academia forever.  Do we really want to be sending these vast numbers of PhD graduates out of the academy and lose all that potential research talent?  That seems like an incredible waste, and even more so when we see how difficult it is to get a positive impact on productivity out of this structure.

Next time: I’ll keep poking at this simulation and see whether these results hold up, and I’ll be doing some other comparisons on other measures, including total research output across different groups.  Early indicators: postdocs increase total research output, and research quality across the population becomes highly unstable.  More later.

 

 

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More Science about Science

After a good few hours working on the simulation yesterday — and by ‘a few’ I mean ’15 hours’ — I have things working in a more stable configuration now.  The original simulation I’m working from was structured around a stable population, but in this simulation I’m using a dynamic population — a very dynamic one, in fact, as postdocs shuffle in and out constantly.

This has meant that I’ve been working a lot on re-writing some of the code to facilitate the addition of postdocs to the virtual research community.  Yesterday I ended up learning some new skills when I found that I needed lists of agents that retained the order of the elements within, so that was an interesting opportunity to learn more about ordered dictionaries in Python.  Presumably I might be able to make use of those in future models too, so that’s very helpful.

So, at the moment we have a nicely dynamic population of simulated academic agents in which postdocs enter the population every semester as grants are disbursed to tenured academics.  Tenured academics spend their time doing research and applying for research grants; they learn from experience and change their time allocation strategies regularly to try to maximise their success in these arenas.  The simulation starts with 100 tenured academics, and after 50 years in a typical run we end up with about ~1200 academics in total, with about a third to a half of those being postdocs, depending on the parameter settings.

These results are based on a generous virtual society though, at least compared to reality: 25% of postdocs get promoted to tenured posts at the end of their contracts; research funding is available to about 30% of academics even as the population grows massively over the years; and tenured academics holding grants get a 50% boost to their research output.  Initially I had included a ‘management penalty’ to research quality for grant-holders, to account for the time spent line-managing postdocs and administering projects rather than actually doing research, but in this generous situation I left that penalty out completely.

So, in this relatively happy situation compared to the real world, do we see any productivity gain from the mass introduction of non-tenured, research-only staff?

Well… no, not quite:

r_mean_pdr

As you can see above, once postdocs are introduced we see a relatively precipitous drop in research productivity.  Grant-holders in particular suffer a great deal on this front, despite having that 50% research output bonus.  Tenured academics not holding grants (in purple) and failed grant applicants (yellow) also dip significantly, but then rebound slightly as they adjust their time allocation strategies between grant-writing and pure research.  Postdocs enter at a lower point and then settle at a middling level of productivity, necessitated by the lowered research productivity they experience at the beginning/end of their contracts.  Their output tends to be more ‘spikey’ in general, as they shuffle in and out of the population very frequently.  Toward the end of the simulation everyone begins to converge between the 0.3 – 0.5 range or so — and in this run we can see the postdocs just overtaking the grant-holders in productivity.

Another interesting aspect here is that in a no-postdoc situation there’s a reasonable positive correlation between research quality and grant disbursement — better researchers tend to get the money, in other words.  When postdocs are introduced that breaks down completely, and there’s little to no correlation between the two; in fact on more than a few runs I’ve seen slight *negative* correlations, this in spite of the fact that in the simulation research quality is used in the ranking of applications.

So — at this stage it seems like introducing a highly volatile, insecure population of researchers into the mix creates a large amount of uncertainty, reduces overall research output, and in general disrupts things significantly.  Even in a ‘generous’ research environment we see these problems clearly.

What about in a more challenging funding environment?  Let’s imagine we’re working in biology or something, one of those fields were grant applications only succeed 10-15% of the time, and money is scarce so permanent positions are even more difficult for postdocs to achieve:

r_mean_pdr

The population is much smaller, sustaining 605 academics in this particular run and just 96 postdocs — but the research output stats look extremely similar.  Grant-holders suffer a huge drop in overall productivity, punctuated by periods of high output when they’re holding that grant, and dipping again when they dump research time into grant-writing to try to get the next one.  Failed applicants and non-grant-holders still hover around the bottom edges, de-emphasizing research as they’re trying desperately to get research money through writing bids.  Postdocs, meanwhile, wobble around the 0.4 mark most of the time, never quite in post long enough to settle in  — and given that they’re not able to apply for grants, they never can benefit from that 50% bonus to output like the senior academics can.

Again these are early results and a very cursory analysis, but it seems like what’s happening here is pretty stable even with fairly significant changes to parameter settings (I’ve done many more runs on my own to check this).  This suggests that in order to escape these problems, future versions of the simulation will need to look at more drastic changes to the research career/funding structures in order to try to address these problems.

Next time, I’ll be adding some more analytical tools to the simulation, and developing some experiments to test alternative funding disbursement methods and career structures.  As ever please do get in touch with me if you have ideas or suggestions — I’m very keen to have more people to speak to about this kind of work!

 

 

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Modelling Research Careers: Very Early Results

I’ve managed to get that research careers simulation up and running today — a very early version, mind you.
Each time grants are disbursed to our simulated academics, the top 10 applicants receive a postdoc.  Postdocs work full-time on research and do not apply for grants.  At the beginning and end of their contracts (which range from 2-5 years long) their output is reduced significantly to account for stress caused by entering a new job or searching desperately for a new one, respectively.  Postdocs have a 10% chance of being made permanent at the end of their contracts; if they’re unlucky then they simply drop out of the system altogether (I haven’t implemented multiple contracts yet).
So what we have is a very volatile situation right from the beginning — we’ve got lots of people on short contracts, most of whom are under significant stress for part, or even all, of said contracts.  Postdocs are constantly being shuffled out of the system and replaced with new postdocs, so the research environment is being filled up with stressed-out people with highly variable levels of research talent — and talented ones are just as likely as crappy ones to be booted out the door at the end of their contracts.  Permanent academic jobs are in short supply, so most postdocs never get a chance to contribute to grant applications.
The results are rather more drastic than I anticipated.  Here are the results for mean research output from a quick run of the simulation including postdocs:r_mean
Contrast that with the below, which shows the mean research output from a run with the same initial conditions but without postdocs in the simulation:
r_mean
 
Mean research output across all categories, no postdocs: ~0.61
Mean research output across all categories, postdocs added: ~0.34
 
Given I wrote all this code in a day, these results are highly speculative at best — but I’m hoping that the final version will give us a decent representation of the impact of competitive funding systems and job instability on academic research quality.   At this point I’m just pleased to see it up and running!
There’s still a ton of work to do: double-checking everything, adding in detailed stats collection on the postdocs, then revamping the funding disbursement functions to tie grants and postdocs together explicitly so I can measure output by project/PI.  There’s a few other bits I really want to do, like implementing multiple contracts, etc.
I’ll keep posting progress reports as I go… please wish me luck!
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Modelling Research Careers: early thoughts

As some of you know already, because I keep going on about it, or worse, trying to drag you into it, I’m hoping to kick off a major project on simulating the research career structure and its effect on scientific productivity.  Having done my time as a postdoc, like many of us, I’m pretty convinced that the current pyramid-scheme structure of academia is not only sub-optimal, but fundamentally damaging, particularly toward academics from marginalised groups.

My first attempt at building an early-stage model of research careers is taking inspiration from Geard and Noble’s paper on Modelling Academic Research Funding as a Resource Allocation Problem.  In this paper the authors construct an agent-based model in which simulated academics attempt to obtain grant funding — frequently a prerequisite for any kind of decent job security these days — by devoting a certain portion of their time to writing proposals for competitive funding bids.  Agents have an underlying research productivity level which influences the perceived quality of their proposal when it comes under review.  At the review stage, top-ranked proposals are funded, and funding is then given to agents (which manifests as an increase in their research productivity).  Agents produce research outputs according to their productivity, whether or not they are holding a grant, and how much research time they have available (given that some period of time must be spent writing grant proposals).

In the end the paper demonstrates that the current system of grant funding is inefficient — huge amounts of time are spent on obtaining grants, which takes away from research productivity, and since most grant proposals are unsuccessful we end up with a lot of time wasted.

What I’m proposing at this stage is to modify this framework to include agents who are on fixed-term research contracts.  Now, presenting a simplified version of the post-doc experience would require a few changes:

  • Agents should be on fixed-term contracts — in the UK about 2/3 of all research-active academics are on FTCs, so the model should reflect this
  • Many postdocs are given much more time to devote to research in general, being largely free of time-consuming teaching or administrative duties
  • Postdocs need to spend significant time during the end of their contracts looking for a new job
  • New postdocs may lose some productive time due to needing to acclimatize to their new working environment
  • Postdocs are often tied to specific projects, and their contracts live and die as the project does

At the moment I’m envisioning a version of the model where we add significant new elements to try and work postdocs into this:

  • FTCs can vary in length from 2 to 10 semesters — as do projects
  • FTC agents don’t contribute to grant proposals, nor do they submit proposals for review (in reality some do contribute, but at least here in the UK postdocs are not considered proper academics by the Research Councils and thus cannot apply)
  • When the postdoc first starts work, 30% of their time is spent adjusting to the new environment, getting to know people and the work that needs doing
  • When the postdoc’s contract is due to end, again they lose 30% of their time due to job-hunting, interviews, and general stressing out
  • When grants are disbursed, the top 10 funded projects are allocated a postdoc with a contract length matching the grant length
  • Postdocs add their research productivity to the academic holding the grant
  • When a postdoc’s contract ends, at the end of the current semester they’re given a 10% chance of being made permanent — allowing them to then conduct their own research programmes, apply for grants and get their own postdocs
  • Postdocs who don’t get made permanent can transfer to another project if one gets funded and needs a postdoc.  If that doesn’t work they drop out of the research population

At the end of a run — say, 100 semesters like in the original model — I’d be looking at overall research productivity, research productivity in postdocs vs permanent faculty, the career history of the postdocs, and the distribution of grant income across the population.

What I’d expect to see is an elite set of agents who started collecting post-docs early, then snowballed their way into a series of successful grants and even more postdocs, while the rest of the population flounders, and is at a serious disadvantage compared to faculty members on the exploiting-the-postdocs train.  As for the postdocs, only a tiny number would be made permanent and thus benefit from their efforts, while a large number would end up on multiple FTCs or dropping out of the population altogether.  All of this would be broadly reflective of reality.  If that were to happen then perhaps this model could provide a good platform for investigating alternative methods of organising research careers, and for examining how different funding disbursement methods affect the fate of postdocs.

What I’m hoping to get out of this in the main is a model which demonstrates the interplay between precarious employment in academia and our current competitive methods of disbursing funding.  Modelling research as a resource allocation problem fits this well, I think, because postdocs are placed under particular pressure to find their next posts in a limited time while being expected to produce substantial research output.

Now as I write this I’m very aware there’s a lot of things at play here and this model is already in danger of being over-complicated.  Even still there’s a number of other factors I’d like to try to address at some later stage, most particularly the impact of stress on research output (from failing to get a grant, worrying about job security, etc.) but let’s just see if this works at all first!

But first: please do chime in if you can and let me know what you think, where I’ve gone wrong, etc.

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Nagel, Enactivism, and Basic Minds

The other day I wrote about beard-spiders and what I thought of them.  Or at least, the things about beard-spiders that I made a mental note to think about at some future time.

Well, that time is now.  Ish.  Probably not, actually, but at least I’m going to write about basic minds, which I started thinking about because of the beard-spiders.

Let me say from the outset that I may very well misuse some terminology, so feel free to correct me in the comments below.  Anyway this really is just a bit of me trying to get a grip on some concepts in a sort of stream-of-consciousness way without drowning myself in jargon, so try not to get too worked up about it.

Nagel’s paper, as I mentioned the other day, has had a remarkable staying power.  In it he takes aim at reductionist theories of mind, which attempt to address the classic mind-body problem of consciousness: what is the relationship between consciousness and subjective experience, and our physical brain and body?  Reductionists want to solve this problem by reducing away the complicated bit of that equation — consciousness.

Nagel argues that no reductionist formulation can eliminate subjective experience — that if we consider some organism to have any level of conscious experience, then there must be “something it is like to be that organism”.  He proposes that attempts to eliminate subjective experience from the problem are doomed to failure:

“[Subjective experience] is not captured by any of the familiar, recently devised reductive analyses of the mental, for all of them are logically compatible with its absence. It is not analyzable in terms of any explanatory system of functional states, or intentional states, since these could be ascribed to robots or automata that behaved like people though they experienced nothing. It is not analyzable in terms of the causal role of experiences in relation to typical human behavior—for similar reasons. I do not deny that conscious mental states and events cause behavior, nor that they may be given functional characterizations. I deny only that this kind of thing exhausts their analysis.”  (p. 436)

The case of the bat appears shortly after this introduction.  If we presume that bats have some level of subjective experience, that there is something it is like to be bat, then we would imagine that their experience is something very different from our own.  Bats have different bodies, different senses, and live in entirely different environs than we humans do.  Even if we amuse ourselves by examining what our lives would be like if we did the things that bats do, it would still be impossible, in Nagel’s view, for us to “know what it is like for a bat to be a bat” — we would still only know what it would be like for a human to be a bat.

This inability to access the experiences of the bat leaves us with a conundrum, if we are to develop a physicalist conception of mind that includes subjective experience.  Nagel argues that experience is something fundamentally irreducible — that unlike other phenomena we might describe with physical theories, subjective experience is impossible to describe in a way which would be comprehensible to another species.  There’s no way to replace the subjective with the objective when it comes to experience.

That’s the core of it, in my view.  I was going to continue here and summarise some more, and then delve into Daniel Dennett’s reply, but that’s pretty irrelevant to this post.  Also I’m lazy.

What interests me still about this paper, despite its age, is that I enjoy its ability to provoke debate and thought despite what is, at its core, a quite simple argument using a very accessible premise.  To me it’s powerful philosophical writing — the author presents his views openly and with clarity, and the topic is explained through a relatable example which gradually builds upon itself until you reach a conclusion.  Whether that conclusion is agreeable or not is up to the reader, but I feel most would agree that at least the journey to reach it was interesting and enjoyable.

So what I hope to do, inspired by Nagel’s example, is to try to understand my own objections to the current way of thinking in cognitive science and philosophy of mind by using a simple example that I can actually grasp.  In cognitive science and philosophy today we see a lot of excitement around enactivism, the view that cognition is not a process undergone by a mind being given a world and imposing concepts and schemas on it, but that it arises from the active engagement of an organism with the world around it.  Organisms engage with the world through sensorimotor interactions with their environment, the world affords us the ability to engage in certain actions — and all this allows us to enact the world and thus experience it.

I’ll be the first to admit that there’s an appealing sense of action (enaction) to this view.  We’re not mere computational machines performing operations on sensory data we’re given by the world — we’re organisms interacting, discovering our environments, moving amongst not a static and lifeless external world, but actually a rich tapestry of information and experience that informs every second of our being.  Sounds great, doesn’t it?

Yet there’s something fundamental in this picture that leaves me wanting.  I’m not sure what it is exactly, but the predominant feeling I get is one of anticlimax.  I guess I remain skeptical that enactivism actually moves us any closer to an understanding of mind and experience, and I feel it simply kicks the mind-body problem can down the lane rather than actually chuck it in the recycle bin.  Or possibly more accurately, rejects the mind-body problem entirely and attempts to replace it with a body-body problem.  I’ve heard various arguments about this from trusted friends on various occasions, but my skepticism remains hard to dislodge.

There’s a few reasons that this might be — I often have trouble unpacking enactivist definitions of behaviour and cognition, for example.  I also have certain objections to the ever-intensifying antirepresentationalist stance which in my view dismisses quite legitimate objections raised even by enactivism-friendly philosophers (Andy Clarke being one example).  But both of these points have been addressed a great deal by others with much greater philosophical acumen than myself, so I’ve been looking for something to talk about that would capture more of my own experiences and interests, and not just be a second-rate Ned Block (among others).

A few years ago I posted briefly about a book that was coming out called Radicalizing Enactivism: Basic Minds Without Content.  When a book releases with a provocative title like that it’s no surprise that tons of interested parties wanted to review it.  The authors come under fire in some of these accounts for their dismissal of the idea that basic minds are capable of sense-making, as this would presume that basic minds are capable of interpretation.  Or something, I’m still reading this stuff.

Some would prefer going all the way down the rabbit hole, and deciding that basic minds can participate in sense-making and that “the problem of mind is that of the problem of life” (Alva Noë, Out of Our Heads, 2009, p. 41).  I’m not sure how to think about this just yet, and I’m hoping some people will direct me toward some interesting debates on this front.*  Others would shy away from that point, leaving the sense-making and content and intentionality to adult human minds.

Either way, I’m filled with questions.  How do we characterise basic minds?  What do enactivists and representationalists make of them, and having had time to work out some examples, what do I think of them?

As far as I can make out, basic minds are an important concept when speaking about enactivism, at least in the Radical Embodied Cognition sort of way espoused by Daniel Hutto and others.  Hutto’s project seems all about characterising cognition as being entirely free of content, or as he puts it, ‘[rejecting] the thesis that Cognition Involves Content, in its unrestricted form’.  My initial reaction to this was immediate and forceful — of course cognition can have content, you weirdo! — but as with everything it depends on how you define content, and cognition for that matter.  In order to understand this project, I also need to understand basic minds and their place in the argument.

That being the case there’s a lot of work to be done on my part to understand exactly what’s being talked about here, and hence my recent nostalgic revisiting of Nagel.  At this point I feel if I’m going to develop an understanding of these concepts I need to follow Nagel and grab a substantive example and follow it through until something illuminates my thoughts more clearly.  More than anything I want to discover the root of my objections and find out whether they hold any water.  It’s quite possible that they don’t, but I feel either way that it’s a process worth going through for my own edification.

As part of this little project I’m building up quite a reading list of books and articles — some of these will be re-acquisitions, like Mind in Life and a few related tomes which have unaccountably vanished from my possession somehow.  In particular I’m interested in Lawrence Shapiro’s Embodied Cognition which apparently spends some time focusing on Randall Beer’s work, and if there’s one thing I’m always happy to do it’s to read about Randy’s papers on minimally cognitive agents.  Other suggestions on minimal cognition and enactivism, basic minds, etc. are more than welcome.

It’ll probably be a little while before my next post, so I’ll leave you with some interesting critiques of enactivism from people who actually know what they’re talking about:

Mineki Oguchi: http://utcp.c.u-tokyo.ac.jp/events/pdf/001_Oguchi_Mineki_3rd_BESETO.pdf

Jesse Prinz (1): www.theassc.org/files/assc/2627.pdf

Jesse Prinz (2): http://subcortex.com/IsConsciousnessEmbodiedPrinz.pdf

EDIT: Another good one from Xabier Barandiaran: https://xabierbarandiaran.files.wordpress.com/2009/07/barandiaran_-_2014_-_enactivism_without_autonomy_-_aisb50-s25-barandiaran-extabs.pdf

*Shout-out here to Tom Froese who pointed me to this quote and related points through one of his papers which I can’t find just now.  You write a lot of papers Tom.

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On spiders and beards

I’ve decided to start using this blog more often for what people often use blogs for — writing down thoughts and ideas, and seeing what comes of them.  I’m going to start by discussing why spiders might like to live in my beard.

Let me explain.  One time I was sat in a pub with a girl.  I was musing on something or other, doing my best to keep up my end of the conversation.  Suddenly the girl started laughing.  What started as a titter became more uproarious, and in response my self-conscious anxiety grew and grew.  What was she laughing at?  Was something wrong with what I was saying?  Did she suddenly realise I look faintly ridiculous, like a short and awkward version of Jesus?  Was she having some sort of boredom-induced brain attack?

Turns out there was a spider in my beard.  She reached over, coaxed it onto her finger, and gently flicked it over onto an empty part of the table.

At this point, several thoughts went through my head:

  1. Why did the spider decide to abseil all the way down from the ceiling into my majestic facial hair?  Did the spider really decide to do this, or was it a consequence of some external factors?  Did my majestic facial hair present an appealing nesting opportunity?  Just what is it like to be a beard-seeking spider?  Are all spiders innately beard-seeking, given the right conditions, or was this a particularly intrepid arachnid?
  2. This girl just touched that spider with her bare hand.  At best I’d use my bare hand only to slap it away from my face while squealing pathetically, despite it being a rather small and wispy spider, all things considered.  What is it about these eight-legged beasts that sends me — and, thankfully, lots of other neurotics — into a frenzy of terror and despair?  What does it say about me that I can face many challenges in life, and yet the mere presence of a tiny arachnid on my face makes me want to cry and scream and leap from the nearest window?  Come to that, what does it say about this girl who not only can tolerate their general ickiness, but actually finds them amusing?
  3. Spiders have eight eyes, but none of them actually see particularly well, at least in the way we’d define it.  They sense motion, light and dark, and that’s about it.  If I were a spider, what would be my experience of a beard?  What would I see, with my vastly different perceptual abilities and eight horrible eyeballs?

Since that fateful day I’ve discovered that my head seems to have a remarkable ability to attract spiders.  Time and time again I’ve been sat somewhere only to find a spider suddenly abseiling down from the brim of my hat in front of my face.  They do so casually, as if they’ve got all the time in the world and they’re not the least bit threatened by the massive hairy mug mere inches away.  ‘Oh, hi!’ they seem to say.  ‘What’s happening?  I’m just hanging out — get it?’

‘Yeeearrgghhh’  I invariably respond, slapping them away from my face in a blind panic.  I’m really not very sociable on these occasions, to my eternal regret, but they keep trying nonetheless.

I was thinking about these spider encounters today, and I wondered idly if, somehow, the spiders got wind of my experience in the pub and the thoughts that followed, and every so often they send an envoy down from my hat to check in and see what I’ve decided about those thoughts.  Maybe they want to have a proper inter-species discussion on their experience of spiderdom, and to share with me their well-developed philosophical traditions.  Perhaps, I thought, I’m slapping them away not out of fear — or at least, not just fear — but out of shame for my lack of action on those thoughts.

I’m sorry, spiders — I promise I’ll get back to work on these questions.  I’m not sure what form these explorations could take — a few years ago I’d envisioned something like Thomas Nagel’s famous article “What is it like to be a bat?”, a 1974 critique of reductionist theories of mind.  I doubt that “What is it like to be a beard-spider?” would be anywhere near as influential as that article, but you never know I suppose.

Regardless, I owe it to myself, and to the spiders, to think more about these questions.  Maybe then they’ll stop dangling off my hats and giving me expectant looks.

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Modelling Research Careers

Thanks to the stimulating discussions that came about during and after the recent Simulating the Social Processes of Science workshop, I’ve been making a start on a research proposal which combines two of my major interests: simulating institutions and social interactions; and inequalities in research careers.

At the moment, my colleagues and I are putting together an executive summary of our idea, which is still taking shape. We hope to develop computer simulations of the current career structure of the academic community, focusing on the recent explosion of insecure short-term contracts for postdoctoral researchers. Here’s a sneak preview of the executive summary:

Motivations

The academic community in the UK has become an increasingly casualised workforce in recent years; some 74% of researchers are on fixed-term contracts. Insecure employment can have significant impact on individual researchers, such as increased stress levels or reduced productivity due to the need to spend significant time searching for further work. However, the systemic impact of this trend on academic institutions and on the broader research community has yet to be investigated in any significant way.

As a result of the prevalence of fixed-term contracts, academic institutions face numerous challenges: a much-increased rate of staff turnover; regular and frequent loss of specialized skill-sets; high costs of training new staff; and the inability to retain skilled young researchers with high potential. More broadly, the academic community as a whole may face a loss of overall productivity as increasing numbers of young researchers lose research time to complications of the career structure, and the consequent lack of sustained, long-term research efforts due to the short-term focus necessitated by fixed-term work. This research programme will examine the impact of the career structure of academia on research productivity using innovative modelling frameworks.

Aside from the obvious self-interest at play here, in that I’m currently stuck in this situation myself, what I find most compelling about this idea is what we may learn about the structural problems of academia. As the use of fixed-term contracts has been increasing, we’ve seen a number of fundamental shifts in the ways that universities operate. We see a much greater emphasis on attracting international students, competing for international recognition, and an ever-expanding management structure which puts academics under constant, ceaseless scrutiny. Understanding the effects of these changes will be a major part of this proposal, and I hope that the insights we gain from this work might help us develop alternative approaches to conducting research — approaches that might help academics regain their autonomy and job security.

The next major step in fleshing out this proposal is to develop our theoretical framework more.  Focusing on the impact of research career structures on research outputs will help us to make the case for this work to potential funders, who will certainly have an interest in discovering how our current structures might be made more productive.  But at the same time, looking more deeply at how these structures have evolved and what institutional changes in universities have facilitated these problems will be more enticing to other working academics who might be interested in collaborating with us.

So, much work remains to be done.  Comments and ideas are always welcome.

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Kill the REF

I found an interesting critique of the Research Excellence Framework by Bill Cooke, which argues that the REF should be killed on the basis of the intrusive prying into personal circumstances that is apparently required to reduce REF outputs for ‘complex circumstances’.

Personally I feel this is just one of many reasons to kill the REF.  The REF seems to me to be a draconian, costly, fundamentally damaging exercise, one that in the end will only succeed in consolidating even more money in universities which already dominate the research landscape.  I fail to see how this is beneficial for UK higher education, when surely the universities on the lower end of the scale could use a leg up in their efforts to become competitive?  Why do we need a mechanism to create even more of a gap between the top and bottom of the league tables?

Meanwhile, this senseless race for money and prestige creates an immense human cost, causing increased stress, workload pressures, and workplace bullying and harassment.  The REF also exacerbates the growing gap between permanent faculty and fixed-term postdocs, as fixed-term academics are completely ignored by REF.  It’s clearly too late now to stop this REF, but I do sincerely hope we can make this the final one.  This whole poorly-conceived exercise does nothing but cause significant damage to the academic community and should be stopped.

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Higher education as a consumer good

I wrote this rant some time ago, when I felt the need to write something about the current state of UK higher education.  I don’t believe I ever put it elsewhere, so I’ll put it here.

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While the current financial crisis looms large, the immediate consequences seem devastating enough: high unemployment; the European debt crisis; collapsing banks and governments.  Yet off in the distance, something insidious lurks: a disastrous and irrevocable change in how we view the most essential elements of our society.

We have all seen and heard by now of the student loan problem that continues to worsen in America.  As it stands now, American higher education has to face the more than $1 trillion in unpaid student loan debt that has accumulated, a staggering figure that begs the question: what happens if it never gets paid?  How, in fact, do we expect new graduates to pay, when youth unemployment continues to skyrocket and increasing numbers of new degree-holders are forced to move back home to save money?

Underlying this, however, is a deeper assumption about the value and the place of education in society.  Education is not a birthright, not something to which anyone of sufficient cleverness is entitled; education is instead a bonus, an indulgence which requires significant financial resources.  

Until very recently, this was not the way higher education was provided in Britain.  University-level education was for many years provided for free, and students were given a small stipend on which to live.  Education was viewed as an investment, the cost society should pay to produce a vital and vigorous younger generation prepared for the challenges ahead.

In the last decade, this noble ideal has eroded away.  Starting with Tony Blair’s controversial introduction of tuition fees, and now culminating in David Cameron’s tripling of those fees, students are now consumers, taking on enormous debt on the promise of receiving a marketable education.  

At the same time, further changes to higher education will alter the criteria used to approve degree-granting institutions, allowing private education providers — the very same currently plaguing America, preying on the disenfranchised and the vulnerable to get student loan money flowing in — to gain a foothold in these isles.  Meanwhile, academic staff are losing their pension benefits, watching their pay stagnate, and seeing their most valued colleagues and assistants culled, all in the name of preserving the bottom line.

All of this is worrying, but more worrying perhaps is our complacency.  We academics sit and watch, wringing our hands fitfully; at best we attempt to fight back in our usual manner: lengthy, wordy diatribes written to an audience of our peers.

But this educational crisis demands more of us than that.  For once we have to crawl out from our laboratories, our studios and studies and basements full of computers, and emerge blinking into the sunlight.  We need to stamp our feet, make some noise, and stop the further degradation of higher education into yet another venue for consumerist greed and bitter, needless competition.

Otherwise we will be left with a system built entirely on the back of student debt, providing our expertise and knowledge for the benefit of an elite who do not care about education or research or discovery.  They will shed no tears for the unprofitable arts department that is cut (or the social work department, in the case of my university).  They will think nothing of cutting unpopular subjects that do not attract sufficient students with their juicy loan checks.  They, like the bankers and the politicians, will bow before the gods of the market in supplication — caring nothing for the students who pay their salaries, and the lecturers, professors and researchers that bring in grants, publish respected papers, and attract well-moneyed students, all while working for peanuts with no retirement plan to speak of.

I moved to Britain some years ago to get my PhD, feeling a certain excitement to be entering a society where education was actually viewed as a public good.  Now, less than a decade later, British higher education stands in the balance.  I like to think that most Britons feel a justifiable pride in the educational achievements of their forebears, and yet here we are in the midst of a government that sees fit to ensure that this venerable education system will be changed forever — and for the worse.  Now, do we sit calmly and suffer in silence — or will we stand up?

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