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AI & the self-driving resume: 2. The resume & the market

This is the second of 3 posts on “AI & the self-driving resume”

In a sense, the job market is really a market in resumes, even though a real person – someone seeking a job, a potential employee – is behind each one. Resumes stock databases, they are digitally searched, they may be passed around and printed and looked over. The distribution of resumes engages intermediary organizations, and advice about how to write and share resumes has become an economic activity. And of course, each resume itself represents an investment of time and resources.

Reign of the resume

HotR The resume, as a statement of one’s experience and education, and nowadays often cast as a marketing tool, is perhaps the central element in the current employment system. While some want to trace the history of the resume back to Leonardo da Vinci (see the diagram at right1), it really only became an established part of job applications well into the industrial age. Despite some changes in standard content over the years (e.g., bio info no longer appropriate, the objective statement now “out of style“), and in availability of much better tools for producing  and disseminating resumes on the one hand and processing them on the other, the basic concept hasn’t changed at all.

The ability to submit resumes has always run into the problem of whether and how they will be read on the receiving end. I still recall a talk back in the late 1970s in which the speaker suggested a red ribbon as a device to make a resume stand out in the very physical pile of paper before a recruiter hiring for entry level positions. Current availability of advice and tools to improve the content and look of a resume are more sophisticated, but still reflect the same concerns. In place of artifices like a red ribbon, job seekers of all levels these days are advised (1) to layer keywords into their resume or CV (one site lists 155) in order to make them findable in the digital pile, and (2) on the chance the resume is seen by human eyes, to format the content for the few fleeting seconds of attention they may get. For more detail, read the 300-page manual on resume writing offered by The Ladders.

Another factor is the disparity between those fleeting seconds of attention, and the hours spent putting together, updating, and tailoring a resume. It naturally takes much longer to write something worthwhile than it does to read it, but it seems that resumes are no longer even read. One quick estimate is that time spent glancing over a resume may be only 0.0003% to 0.0014% of the time taken to prepare it.

Meanwhile, the same digital technologies that have facilitated producing and editing resumes on the one hand, and online job listings on the other, have fostered a kind of trade in resumes. It is possible to post a resume on a website where, if one is to believe the advertising, it will be “exposed” to hundreds of thousands of employers. ResumeRabbit.com, for instance, claims over 1.5 million (via reposting to 89 other sites). It will however be one of probably millions vying for attention.

Even on a more specialized level, the numbers are incredible: DevelopmentAid.org for example, offers a “CV broadcast” service reaching 30,205 organizations (as of April 2017 – the number varies). In short, the system is flooded with ever more resumes.

Where is all this going?

One could argue that the humble resume is in effect being asked to do much more than it was ever intended to do. No surprise therefore to see radical-sounding prognoses such as the “death”  of the resume (for example in 2013, the previously cited 2015 list, and of course Nelson Wang’s 2012 book, The Resume is Dead), perhaps along with its recent counterpart, the applicant tracking system (ATS) .

Discussions of the “death of the resume” propose alternatives such as bios, videos, graphics, or the amorphous online personal brand. One blog post by Charles Handler several years ago suggested that “various elements of a resume are being teased apart and presented in a different format that is based more on profiles and portfolios.” But all these tend to end up with resume-surrogates that still have to be created by job seekers, and then sorted through and processed by recruiters, who for their part resort to the assistance of specialized software.2

In fact, the resume was never “alive” to begin with, given that it is static information on a page(s). Social media presence may be more current, and other resume-surrogates may have their appeal (some of them are quite creative in what they can convey), but in the end, these are all passive presentations of information, regardless of how well-crafted they may be.

Hence one of the questions here: Could artificial intelligence (AI) bring the resume to life, able to interact with a human or machine reader, bring forth relevant information, learn from the interaction, and inform the owner of the resume?

Mass market & upmarket

There is arguably an inherent dysfunctionality to this system, of which resumes are central, as the volume of applicants and positions grows. In the massifying job market, more people can send applications – relatively more easily thanks to technology – to more organizations for more positions. So, hiring departments adapt with more automated ways to screen out digital documents and reduced time for eyes-on review. But even if job seekers  “load” their resumes with keywords to get through the automated screening, the software is also “raising the bar,” to screen in more sophisticated ways. An extreme outcome of this “keyword arms race” is the oft-cited case where one company screened 29,000 applications for a single engineering position with not one of them found qualified.

Suggestions per Nelson Wang and others that job seekers take unorthodox strategies – the new “red ribbon” – are only an advantage when a few are using them. How much does anyone stand out if everyone is standing out, and how can recruiters with limited time sort through the cacophony? There are human limits. Hence on the recruiter side, automation and discussion of “AI” to deal with applicant data – which in turn reduce the applicant, or actually their resume, to data.

This massification of the job market is exactly the kind of situation – large and increasing number of actors, large but varying numbers and types of openings, complex quantitative and qualitative data, and waste – where a more intelligent, if not interactive, program or automation could do much better for everyone.

As one moves up the scale to more specialized and executive positions that are relatively fewer in number and higher in pay, the dynamic changes in some respects. Recruiters, sometimes from executive search services (headhunters) or firms specializing in particular professional fields, may reach out to contact prospective hires. Personal contacts developed in earlier work, may prove useful as sources for information and/or references – and indeed important as many positions on higher levels are not advertised (this is another issue that I’ll come back to). But there are still many people chasing mid to higher level positions in the same job market, relying on basically the same methods and advice.

Imperfect information & intermediaries

The job market is one of imperfect information – in several ways. A job seeker can’t know all available positions they qualify for, and even the best research on a potential employer goes only so far. Recruiters must judge candidates based only on resumes first (usually) and whatever other information comes in the application or via referrals, and they often – especially in some industries – are dealing with a subset of potential candidates they’ll never have the chance to consider.

So, another part of the system includes intermediary entities designed in one or another way to help link employers with job seekers in that uncertain environment:

  • Recruitment firms (“recruiters” may work for specific employers or for one of these firms) and headhunters;
  • Employment or staffing agencies;
  • Job or career coaches;
  • Online job boards;
  • Resume/CV writing services; and
  • Software companies.

All of the above (except for job agencies run by government or non-profits) are businesses, basically selling services to employers, job seekers, or sometimes both. Like any business, they seek to maximize income, minimize expenses, and provide services that attract (and in some cases, retain) customers.  Significant amounts of money and attention to diverse revenue streams (often from both recruiters and job seekers) are involved.

On the job seeker side, for instance, resume writing services run about $100, while job coaches cost clients hundreds or thousands of dollars, with one upper end service costing about $10k (and all of that without any guarantee of results). No figures on what recruiters pay for services in this subsector (in tandem with their in-house recruitment capabilities), but it likely is a lot.

Enter AI

So, we have a system that has grown in all respects, has costly inefficiencies, and is – along with all of us – in the midst of technological change including what we call AI. It is inevitable that some aspects of AI will be brought into the job market more fully, even as other aspects of AI are applied to automate various jobs. We already see the early stages of this, as mentioned in the previous post in this series. The next post will focus on AI, with particular attention to the less often considered subject of what it might do for the job search side of the system, and how it could change interaction between job seekers and recruiters.


1. Image source: Undercover Recruiter. Image credit: Rezscore.com. Click on image to open full size. (Note the 400-year gap in the “500 year evolution.”)
2. Since traditional resume-based approaches on the entry level may miss talent, some employers try to get away from the resume, even using social events or computer games to evaluate applicants. It is not entirely new to have such live-performance evaluations of candidates – the US Department of State has long used an observed role-playing exercise as part of the selection process for Foreign Service Officers.

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AI & the self-driving resume: 1. The future of the job market

This is the first of 3 posts on “AI & the self-driving resume”

There’s lots of speculation these days about how robots and artificial intelligence (AI)* might further transform the way we work or drive a new industrial age – along the way maybe even taking our jobs – but not so much on how such advanced technology could change the ways recruiters fill positions and almost nothing how it might help people find employment. In an age where self-driving cars are already on the road, aren’t we due for some breakthroughs in the mechanisms recruiters and job hunters use in the job market?

Source: Ziptopia, “Take the Wheel, Robot. Self-Driving Cars are Really Happening.” Image credit: Motor Authority

Maybe you’ve read about the novella “co-written” by AI that fared well in recent a Japanese literature competition? Or other projects using AI to write reports or stories – or even “better emails“? If I’m writing a resume, I’d want something along these lines to fill in all the right details and keywords to the right measure, and optimize it just right for the recruiter’s database search and eventual 6 or 8 (or maybe 30 on a slow day) seconds of attention.

But wait – if I’m a recruiter I might want something along the lines of that Alphago program that beat human champions at the complex game of “go” to analyze candidates’ skills and track record and figure out which ones fit best in which positions, seeing ahead a few moves to future development and retention. So maybe even award-winning resumes won’t be seen by humans?

But then, since we’re talking about AI, maybe the resume writing program and and the recruitment strategy program could somehow just talk to each other? Have them get back to us when they have something!

Getting real … in the age of AI

It’s hard not to speculate about what AI might be able to do to make both the job search and the recruitment process less labor intensive, more efficient, and more productive for all.

In recent years there has been a lot of discussion of how technology trends will affect job hunting and recruitment – for example 6 or 7 ways in 2012, 5 ways in 2013, reiterated in 2014, 10 more in 2014, 4 or 5 or 10 ways in 2015. However, all of these really concern changes in, not of, the system, and don’t venture into how cutting edge technology could transform the job market. Yet.

AI actually does come up in a few discussions of technology for recruitment – for example as early as 2008 and in a later undated article –  but more as sophisticated ways of searching resume databases and beyond. A recent article tacks on chat bots and employee onboarding to the tasks AI might do for recruiters, so you can see the direction things are moving in.

There’s not even that much for job seekers, who are for the moment still stuck essentially with late 20th century tools and processes. A recent innovation for job boards claims to use AI to help job hunters find positions. Again an intimation of where things might go, but again not changing the search process, let alone the vehicles used to apply – such as hand-typed resumes.

A system on the verge of transformation?

Could we be on the cusp of a revolution in the job market involving AI, data science, and perhaps virtual reality that could aid both the person looking for employment and the company doing hiring? One that would enable a lot of the time-consuming processes involved in searching and application on the one hand, and review and screening on the other to be done more quickly and systematically, with less human error, and on a wider scale than is possible with current methods?

This is not to suggest that the whole hiring process should or could be completed without human input, but rather that many of the initial (often repetitive) tasks on both sides could be more efficiently and productively handled by intelligent automation – processes that ultimately will be able to interact. And that that human input would then come in where it is most valuable, and indeed essential: input of information and parameters at the outset, and at key decision points later on.

If self-driving cars can provide personal transportation that is potentially safer and more efficient, couldn’t there be analogous advances in how jobs are found and filled?

On the job seeker side, consider how much time goes into searching listings, filling out applications, crafting resumes, writing cover letters, and maintaining a professional social media presence. And along the way keeping up with all the advice and evolving thinking on approaches and techniques to do all of that better, which has become an industry in itself (looking for a job? here’s a list of 9 more books you should read, according to Business Insider).

Altogether this represents a lot of repetitive work, most of which has no return (one recent article on “1200 job rejections” illustrates the problem). What if much of this could be automated, intelligently? Could AI, informed and tasked by a person, search out particular kinds of openings (roles, companies, locations), write and tailor presentation of professional information, and generate job applications? As a learning (recursive) program it would be designed to adapt, but a key aspect would have to be iteration and course correction with the person it is representing.

On the recruiter side, consider how many applications are received for each position, with the numbers growing each year. Incoming applications have to be processed in limited time, or stored in an applicant tracking system (ATS) and accessed as data (think keyword searches of masses of resumes). And then there’s screening and checking references. What if incoming applications could be analyzed and queried, with preliminary background and reference checks as appropriate, to yield a short list? What if the ATS was smart enough to do all that?

Then there is the question of how AI in the service of job seekers and AI in the service of recruiters would work together. One would imagine the need for a system of protocols and a conceptualization of the virtual space in which they would interact, as intelligent agents (IAs) in a multi-agent system. That could in turn lead to radical changes not only in how jobs are found and filled – for one thing, IAs operating quickly and across cyberspace could find matches that people could not – but perhaps also in the ways careers and staffing are approached. One could be permanently on the market in the sense that the IA could regularly check new employment opportunities or potential new hires.

And perhaps lead also to novel outcomes as IAs go to work: What if for example, IAs of job seekers who have never met could compare notes about an organization or salary offers, or IAs of recruiters could share data on a particular candidate?

Reimagining the job market

JMotFThe idea of technology fundamentally changing the ways people find employment and organizations find employees – as opposed to enhancing or modifying parts of the current system – is not new. Perhaps the most extensive effort to think through the possibilities is that of James Cooke Brown in his 2001 book, The Job Market of the Future: Using Computers to Humanize Economies. But while Dr. Brown’s work considers how to reorder the economy and thus the nature of employment, aided by computer technology, I’m wondering if the sequence will actually be reversed. That is, that application of advanced information technologies – specifically AI – in the service of individual employers and especially individual potential employees might in turn change the nature of those relationships and how careers are built.

The job market as we know it is basically an evolution of communication between people needing paid work and people needing help with getting something done. And the current system of web-based applications and screening of digital resumes is the contemporary version of a set of tools, roles, and modes of communication developed in recent history as economies became more complex: job ads; employment agencies and websites; applications with resumes and cover letters; recruitment/hiring as a specialization within the field of human resource management; and processes of review and selection.

Will intelligent technology rewrite this sequence and the elements involved? I’m suggesting it will, and that it will be a good thing. In the following posts in this series, I’ll explore aspects of this question:


* AI can refer to a range of capabilities and processes. For a basic introduction, see the articles in Encyclopaedia Britannica and/or Wikipedia. In referring to AI in this blog post, I am assuming some variable sub-set of that range.

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New categories & LinkedIn archive

With the previous post I introduced two new categories to this blog, both of which represent interests, experience, and areas for exploration (although not necessarily formal expertise):

  • habitat & community – brings the dimension of built environment and how we live in it more explicitly into the set of “multidisciplinary perspectives;” it facilitates discussing the urban side of development as much as the rural, as well as diverse aspects of planning and resource management
  • roads & streets – brings the dimension of physical connections between and divisions within inhabited places, as well as a class of systems and socio-economic dynamics (all of which may be on a cusp of change to the extent that autonomous vehicles and airborne alternatives become more viable).

I’m also adding two others that will eliminate use of the default category “Uncategorized”:

  • about (this blog) – to which this post and articles previously tagged “about this blog” will be moved
  • personal – this will include articles with biographical content

There will also be some upcoming minor revisions of the pages listed in the header.

Addendum, 10 March 2017

I’ve moved the page in header for my other older blog, Beyond Niamey, under Other blogs. Also under the latter is a new page listing articles and some smaller posts made on LinkedIn, which are being copied over.  The latter is kind of an archive, since content and features on such social media sites can disappear.

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Çatalhöyük & a line from Kōbō Abe

In the Neolithic town at Çatalhöyük in what is now south-central Turkey, “The houses were … built so close to each other that it was impossible to pass between them. … It’s thought that the roofs of the houses provided the paths and sidewalks to traverse the community.” This description by Prof. Steven Tuck in his “Cities of the Ancient World” course, called to mind a passage somehow remembered from a translation of Kōbō Abe‘s Red Cocoon1:  “I slowly walk along the narrow crack dividing house from house ….”

Rendering of mural in Çatalhöyük that some say shows nearby mountains and a kind of map of the community. Adapted from Image by: Schmitt AK et al. Source: Sci-News.com.

I don’t recall reading the rest of Red Cocoon but the image that sentence2 evoked was of some slightly surreal cityscape where one could walk along the flat roofs of adjacent dwellings inhabited by mostly unseen people. Perhaps that image was shaped by memory of the scenario in another one of Abe’s works, Woman in the Dunes, where the main characters (one unwillingly) were confined in a space below a barely known community above. Or perhaps by my brief experience on rooftops in Djenné, Mali, even though the houses I lived in were not connected and (unlike the solitary wandering and wondering of Red Cocoon‘s protagonist) there was a certain social nature , although somewhat circumscribed, to that level of city living.3

Artist’s impression of Çatalhöyük. Image credit: Dan Lewandowski. Source: Sci-News.com.

In any event, here was a city that, strangely enough, seems to have been laid out along lines similar to what I’d once imagined from Abe’s line about “the narrow crack dividing house from house.” Çatalhöyük’s particular organization of habitat (bunched together so that one entered each one from above) and social space (the adjacent roofs of the nearly joined houses), doesn’t conform with basic assumptions we have about the fundamental layout of living space and community. And it raises a number of questions, many of which – about why people pioneered urbanization in this place, and how their town worked – have been examined by archaeologists such as Prof. Tuck.

One question that interests me is whether “street” (as opposed to path) hadn’t yet been invented – rather analogous to the concept of “zero” in mathematics. People knew probably all too well what “nothing” was, or wasn’t, but it didn’t have any practical use once you had something that could be counted. Perhaps similarly, anyone could see that there could be a space between two houses, but maybe it didn’t occur to use that for anything other than another dwelling (which would have the advantage of keeping the continuity of roof spaces above, and eliminating the risk of people or things falling into the gap).

Obviously imagining a lot here, but the idea of streets as something that had to be thought of has actually been discussed regarding a much later period of history. In an essay entitled “The Discovery of Streets,”4 J.B. Jackson takes us from the ancient but definitely post-Çatalhöyük small city with its “flexible and informal network of alleys, blind alleys, flights of steps, and paths,” through the evolution (focused here on Europe) of markets and spatial needs, to the eventual use of streets in planning and reshaping communities (which he ultimately connects with the freeway, which I always associated with paths and old turnpikes, but that’s another subject). The turning point he sees as having happened in 11th century Europe:

the discovery of the street as a determinant of city growth and development had by the end of the century produced increasingly orthogonal town patterns, based on right angles and perpendicular lines …

So it does seem as if one could also suggest an “invention of the street” or perhaps “discovery of the alley” some time after Çatalhöyük. And by extension, that perhaps there might be concepts of urbanization that we, for all our sophistication, haven’t yet thought of (or maybe even contexts in which the ancient model from Çatalhöyük might turn out to be useful).

Returning to Abe’s walking along the “narrow crack dividing house from house,” with benefit of Jackson’s discussions of space in Old World cities, there is another interpretation (which likely was obvious to other readers): the “narrow crack” was in fact a narrow street between rows of houses. But it still was more fun to imagine it the other way.


1. Japanese title: 赤い繭 (Akai Mayu), published 1950 or 1951. There have apparently been two translations into English, one by John Nathan in 1966, and the other by Lane Dunlap in 1987. Needless to say, Abe’s story line goes in an entirely different direction than what preoccupies me here.
2. Retrieved from Abe’s obituary in the New York Times (23 Jan. 1993). I did not find the story available online.
3. During the hot season, people would often sleep on their roofs – but when you wake up in the morning on your roof, you always ignore neighbors who are awakening on theirs (in general one never says “good morning” to someone before they’ve had a chance to at least wash their face and take care of their morning essentials anyway). Also one doesn’t peer over the edge of one’s roof into the adjacent courtyards. As such this was different rooftop environment than either Çatalhöyük or what I imagined from that line in Red Cocoon.
4. J.B. Jackson, “The Discovery of the Street,” in N. Glazer & M. Lilla, eds. The Public Face of Architecture: Civic Culture and Public Spaces, The Free Press, 1987. An article in The Atlantic about this essay by Charles R. Wolfe – “City Life: Revisiting J.B. Jackson’s ‘The Discovery of the Street’” – is a useful complement.

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International Mother Language Day 2017 & the Linguapax Prize

The 18th annual International Mother Language Day (IMLD), observed today (21 February 2017), has as its theme, “Towards Sustainable Futures through Multilingual Education,” which seems to carry on the focus on language in education from last year (presumably still with an eye on Sustainable Development Goal #4).

The definition of multilingual education given on UNESCO’s IMLD page is worth copying here…

Multilingual education facilitates access to education while promoting equity for populations speaking minority and/or indigenous languages, especially girls and women:     

  • It emphasizes the quality of teaching and learning with a focus on understanding and creativity;
  • It reinforces the cognitive aspect of learning by ensuring the direct application of learning outcomes to the learner’s life through the mother tongue;
  • It enhances dialogue and interaction between learner and teacher by allowing genuine communication from the beginning;
  • It facilitates participation and action in society and gives access to new knowledge and cultural expressions, thus ensuring a harmonious interaction between the global and the local.

Linguapax Prize

This year’s Linguapax Prize, announced today (as it is annually, on IMLD), was awarded to Dr. Matthias Brenzinger, a German linguist specializing in African languages (notably non-Bantu click languages) and endangered languages, who is currently at the University of Cape Town and heads the Centre for African Linguistic Diversity (CALDi), which he founded. Dr. Brenzinger has also worked in Japan.

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Two language museums in Washington

PW logoOn the eve of International Mother Language Day (IMLD), here’s a quick look at the news that the Washington, DC area will get a second museum dedicated to languages: Planet Word Museum. This project began several years ago, based on the vision of Ann B. Friedman, a philanthropist and former reading instructor, and was incorporated in 2013 as the Museum of Language Arts, Inc. On 25 January 2017, the DC Office of the Deputy Mayor for Planning and Economic Development announced an agreement by which (pending DC Council approval) Planet Word and its partners will convert an old landmark school building into a museum space. Opening is planned for 2019.

PW logoThe first museum in this genre in the DC area, and in the entire United States, is the National Museum of Language (NML), which despite the name is also a private non-profit venture. Its origins go back to Dr. Amelia C. Murdoch and a “group of expert linguists, language specialists, and language enthusiasts” in 1971, but it wasn’t until 37 years later that a small museum space was opened in College Park, Maryland (Multidisciplinary Perspectives featured an article about their opening in 2008). Unfortunately, the recurring cost of the museum space turned out to be too high to maintain, so in 2014, NML closed its permanent exhibit and shifted to a strategy of moveable exhibits, an enhanced online presence, and other activities.

A tale of 2 museums

The first question that comes to mind on learning of the new language museum project in this metro area, is whether it and the older one are in communication. The answer, according to NML president Dr. Jill Robbins, is yes.

A second question or set of questions has to do with the relationship between the two – both in terms of missions (similarities, differences, complementarities), and in terms of practical links (such as connections among people working on the two different projects). These seem to me to be harder to answer. In part that is because one is new and the other still relatively young. And there are other differences between the two that would figure in any collaboration.

In terms of their respective missions, my impression is that NML is somewhat more focused on aspects of language diversity or “unity in diversity” (the themes of the museum include “universal aspects of language,” “language in society,” and “languages of the world”). Among various exhibits, they have done some interesting work presenting dialect research in the US, for example. From NML’s mission statement:

Our mission is to inspire an appreciation for the magic and beauty of language. We seek to lead our visitors to their personal discoveries of language and languages. …

My impression is that Planet Word is somewhat more concerned with language arts (note the incorporated name mentioned above) and applied linguistics. Literacy figures as “The Big Issue” on their “About” page. We can expect more details as the project develops, but in the meantime, an article in Chronicle of Higher Education by Planet Word board member Prof. Anne Curzan offers some insights into their thinking. Planet Word’s vision (from the About page):

Language is what makes us human. From earliest childhood we weave our words into speech to communicate. At Planet Word we inspire and renew a love of words and language through unique, immersive learning experiences.

On the organizational level, there are some obvious differences. For example, Planet Word is clearly able to access funding at a level several orders of magnitude above what NML has ever obtained. It also has a much larger board with a wider geographic and institutional representation than the smaller NML has.

On the other hand, NML has a significant experience with the practicalities of running a language museum – albeit on a smaller scale than Planet Word evidently aspires to – and in developing relations with educators and institutions in its vicinity and more widely. The latter include, for example being a founding member of the International Network of Language Museums (INLM; see also addendum, below), participating in events such as the IMLD 2013 celebration at the Bangladesh embassy in Washington, DC, and having a wall exhibit – about American lexicographer Noah Webster – on display at the Noah Webster House in West Hartford, Connecticut.

From the descriptions, however, it seems that Planet Word is modeling itself on certain larger museums – the National Museum of Mathematics in New York was mentioned in one article. Also, Planet Word is expected to have a major impact on development of its immediate neighborhood (see article in City Lab, which includes a comparison with the National Building Museum in DC) – not a role that NML has had to play.

All that said, these two language museums do occupy much of the same terrain even as their emphases and some of their angles may differ. The field of study of language(s) and linguistics after all is broad, and there are diverse approaches to organizing museums. So basically, it’s no surprise that “language museum” can mean different things.

A question at this point is what kind of collaboration might be possible and make sense from the points of view of NML and Planet Word, and also for the public, for whom even one language museum is still a novelty.

We’ll see how this develops, but it will be interesting to see an interview of Ms. Friedman that I am told is planned for publication on the NML website. One question I’d like to ask of both efforts is how they would celebrate IMLD, an annual observance that is not that well known in the US.

Addendum (Feb. 21)

Thanks to NML’s Dr. Robbins for feedback on this post as originally published, leading to some corrections to copy and also a clarification on her institution’s range of activity (which I further expanded on). A key element in that range is the INLM (a list of the members of which appears in an NML blog post).

In the interests of economy, I did not get into the subject of language museums worldwide in this post, even though they figured prominently in my compilation of resources on the International Year of Languages 2008. The global dimension of this class of museums (within the larger class of “locations” about language, to use David Crystal‘s term from “LADDA“) is to a certain extent unavoidable (some articles about Planet Word have mentioned the Mundolingua in Paris, for example), but important enough to merit a separate discussion.

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