Tag Archives: history-is-a-feature-not-a-bug

Items of some interest:

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These are my recent Pin​board​.in links:

  • Nicholas Rombes: Punk | berfrois

    “Most iron­i­cally, being based in the hope­lessly lost cul­tural void of Ann Arbor, a noto­ri­ous mecca for the last sur­viv­ing rem­nants of the pseudo-​​intellectual street peo­ple move­ment that said much and accom­plished little…”

    punk history-​​is-​​a-​​feature-​​not-​​a-​​bug cultural-​​dynamics ha-​​ha-​​only-​​semiserious

  • [1112.5309] POWERPLAY: Train­ing an Increas­ingly Gen­eral Prob­lem Solver by Con­tin­u­ally Search­ing for the Sim­plest Still Unsolv­able Problem

    An amus­ing col­lec­tion of what seem to be half-​​remembered ideas gleaned from his visit to the GPTP work­shop in Ann Arbor two years ago, pre­sented as his own inven­tions and with­out cita­tion or men­tion of the dozen peo­ple who actu­ally do this work. His keynote, as I remem­ber it, essen­tially revolved around him point­ing out how influ­en­tial his work should have been all along, if only we had both­ered to cite him as we should have done, because he thought up the core con­cepts of genetic pro­gram­ming well before any of us claimed we had. This is pretty much a camel’s-back straw for me. If there is a bet­ter argu­ment for com­pletely boy­cotting the cita­tion sys­tem and rely­ing on per­sonal asso­ci­a­tion and named schools rather than pub­li­ca­tion, I have not yet encoun­tered it. So remem­ber poor oppressed grad­u­ate and post­doc kids: when I cite your work by sim­ply nam­ing you per­son­ally, and not your advi­sor or your insti­tu­tion, and not even your pub­li­ca­tion or jour­nal but merely YOU PERSONALLY, it’s because you per­son­ally deserve the credit, not any of those other leeches. Got that?

    now-​​this-​​really-​​pisses-​​me-​​off-​​to-​​no-​​end

  • [1203.0856] Online Dis­crim­i­na­tive Dic­tio­nary Learn­ing for Image Clas­si­fi­ca­tion Based on Block-​​Coordinate Descent Method

    “Pre­vi­ous researches have demon­strated that the frame­work of dic­tio­nary learn­ing with sparse cod­ing, in which sig­nals are decom­posed as lin­ear com­bi­na­tions of a few atoms of a learned dic­tio­nary, is well adept to recon­struc­tion issues. This frame­work has also been used for dis­crim­i­na­tion tasks such as image clas­si­fi­ca­tion. To achieve bet­ter per­for­mances of clas­si­fi­ca­tion, experts develop sev­eral meth­ods to learn a dis­crim­i­na­tive dic­tio­nary in a super­vised man­ner. How­ever, another issue is that when the data become extremely large in scale, these meth­ods will be no longer effec­tive as they are all batch-​​oriented approaches. For this rea­son, we pro­pose a novel online algo­rithm for dis­crim­i­na­tive dic­tio­nary learn­ing, dubbed textbf{ODDL} in this paper. First, we intro­duce a lin­ear clas­si­fier into the con­ven­tional dic­tio­nary learn­ing for­mu­la­tion and derive a dis­crim­i­na­tive dic­tio­nary learn­ing prob­lem. Then, we exploit an online algo­rithm to solve the derived prob­lem. Unlike the most exist­ing approaches which update dic­tio­nary and clas­si­fier alter­nately via iter­a­tively solv­ing sub-​​problems, our approach directly explores them jointly. Mean­while, it can largely shorten the run­time for train­ing and is also par­tic­u­larly suit­able for large-​​scale clas­si­fi­ca­tion issues. To eval­u­ate the per­for­mance of the pro­posed ODDL approach in image recog­ni­tion, we con­duct some exper­i­ments on three well-​​known bench­marks, and the exper­i­men­tal results demon­strate ODDL is fairly promis­ing for image clas­si­fi­ca­tion tasks.”

    image-​​analysis image-​​segmentation algo­rithms nudge-​​targets

  • [1203.3271] The ther­mo­dy­nam­ics of prediction

    “A sys­tem respond­ing to a sto­chas­tic dri­ving sig­nal can be inter­preted as com­put­ing, by means of its dynam­ics, an (implicit) model of the envi­ron­men­tal vari­ables. The system’s state retains infor­ma­tion about past envi­ron­men­tal fluc­tu­a­tions, and a frac­tion of this infor­ma­tion is pre­dic­tive of future ones. The remain­ing non­pre­dic­tive infor­ma­tion reflects model com­plex­ity that does not improve pre­dic­tive power, and rep­re­sents the inef­fec­tive­ness of the model. We expose the fun­da­men­tal equiv­a­lence between this model inef­fi­ciency and ther­mo­dy­namic inef­fi­ciency, mea­sured by the energy dis­si­pated dur­ing the inter­ac­tion between sys­tem and envi­ron­ment. Our results hold arbi­trar­ily far from ther­mo­dy­namic equi­lib­rium and are applic­a­ble to a wide range of sys­tems, includ­ing bio­mol­e­c­u­lar machines. They high­light a pro­found con­nec­tion between the effec­tive use of infor­ma­tion and effi­cient ther­mo­dy­namic oper­a­tion: any sys­tem con­structed to keep mem­ory about its envi­ron­ment and to oper­ate ener­get­i­cally effi­ciently has to be predictive.”

    mod­el­ing philosophy-​​of-​​science information-​​theory physics ther­mo­dy­nam­ics talking-​​about-​​a-​​model-​​is-​​a-​​model pragmatism-it-ain’t

  • [1203.3434] On the Impact of Infor­ma­tion Tech­nolo­gies on Soci­ety: an His­tor­i­cal Per­spec­tive through the Game of Chess

    “The game of chess as always been viewed as an iconic rep­re­sen­ta­tion of intel­lec­tual prowess. Since the very begin­ning of com­puter sci­ence, the chal­lenge of being able to pro­gram a com­puter capa­ble of play­ing chess and beat­ing humans has been alive and used both as a mark to mea­sure hardware/​software pro­gresses and as an ongo­ing pro­gram­ming chal­lenge lead­ing to numer­ous dis­cov­er­ies. In the early days of com­puter sci­ence it was a topic for spe­cial­ists. But as com­put­ers were democ­ra­tized, and the strength of chess engines began to increase, chess play­ers started to appro­pri­ate to them­selves these new tools. We show how these inter­ac­tions between the world of chess and infor­ma­tion tech­nolo­gies have been her­ald of broader social impacts of infor­ma­tion tech­nolo­gies. The game of chess, and more broadly the world of chess (chess play­ers, lit­er­a­ture, com­puter soft­wares and web­sites ded­i­cated to chess, etc.), turns out to be a sur­pris­ingly and par­tic­u­larly sharp indi­ca­tor of the changes induced in our every­day life by the infor­ma­tion tech­nolo­gies. More­over, in the same way that chess is a mod­eliza­tion of war that cap­tures the raw fea­tures of strate­gic think­ing, chess world can be seen as small soci­ety mak­ing the study of the infor­ma­tion tech­nolo­gies impact eas­ier to ana­lyze and to grasp.”

    touch­stones his­tory algo­rithms history-​​of-​​science computer-​​science

  • Share Books | berfrois

    “Libraries are a recog­ni­tion that schol­ar­ship and cul­ture are more than the busi­ness of cre­at­ing and con­sum­ing. They are a human con­ver­sa­tion, and libraries pro­vide com­mon ground where that con­ver­sa­tion can take place and be remem­bered. By tak­ing aim at the right for the pub­lic to main­tain this con­ver­sa­tion and its mem­ory, pub­lish­ers have shown us what we have to lose. It’s time we resisted the out­sourc­ing of our com­mon her­itage by occu­py­ing the library.”

    Occupy libraries intellectual-​​property open-​​access public-​​policy activism

  • [1112.3307] Poly­tope Codes Against Adver­saries in Networks

    “Net­work cod­ing is stud­ied when an adver­sary con­trols a sub­set of nodes in the net­work of lim­ited quan­tity but unknown loca­tion. This prob­lem is shown to be more dif­fi­cult than when the adver­sary con­trols a given num­ber of edges in the net­work, in that lin­ear codes are insuf­fi­cient. To solve the node prob­lem, the class of Poly­tope Codes is intro­duced. Poly­tope Codes are con­stant com­po­si­tion codes oper­at­ing over bounded poly­topes in inte­ger vec­tor fields. The poly­tope struc­ture cre­ates addi­tional com­plex­ity, but it induces prop­er­ties on mar­ginal dis­tri­b­u­tions of code vec­tors so that validi­ties of code­words can be checked by inter­nal nodes of the net­work. It is shown that Poly­tope Codes achieve a cut-​​set bound for a class of pla­nar net­works. It is also shown that this cut-​​set bound is not always tight, and a tighter bound is given for an exam­ple network.”

    cryp­tog­ra­phy pri­vacy algo­rithms nudge-​​targets network-​​theory com­mu­ni­ca­tion

  • [1203.3353] Solv­ing Struc­ture with Sparse, Randomly-​​Oriented X-​​ray Data

    “Single-​​particle imag­ing exper­i­ments of bio­mol­e­cules at x-​​ray free-​​electron lasers (XFELs) require pro­cess­ing of hun­dreds of thou­sands (or more) of images that con­tain very few x-​​rays. Each low-​​flux image of the dif­frac­tion pat­tern is pro­duced by a sin­gle, ran­domly ori­ented par­ti­cle, such as a pro­tein. We demon­strate the fea­si­bil­ity of col­lect­ing data at these extremes, aver­ag­ing only 2.5 pho­tons per frame, where it seems doubt­ful there could be infor­ma­tion about the state of rota­tion, let alone the image con­trast. This is accom­plished with an expec­ta­tion max­i­miza­tion algo­rithm that processes the low-​​flux data in aggre­gate, and with­out any prior knowl­edge of the object or its ori­en­ta­tion. The ver­sa­til­ity of the method promises, more gen­er­ally, to rede­fine what mea­sure­ment sce­nar­ios can pro­vide use­ful sig­nal in the high-​​noise regime.”

    structural-​​biology image-​​analysis crys­tal­log­ra­phy algo­rithms inverse-​​problems nudge-​​targets sta­tis­tics

  • [1203.3203] An effi­cient algo­rithm for gen­er­at­ing AoA networks

    “The activ­i­ties, in project sched­ul­ing, can be rep­re­sented graph­i­cally in two dif­fer­ent ways, by either assign­ing the activ­i­ties to the nodes ‘AoN’ directed acyclic graph (dag) or to the arcs ‘AoA dag’. In this paper, a new algo­rithm is pro­posed for gen­er­at­ing, for a given project sched­ul­ing prob­lem, an Activity-​​on-​​Arc dag start­ing from the Activity-​​on-​​Node dag using the con­cepts of line graphs of graphs.”

    sched­ul­ing operations-​​research algo­rithms graph-​​theory

  • [1203.3341] A Com­par­i­son of Multi-​​Parametric Pro­gram­ming, Mixed-​​Integer Pro­gram­ming, Gra­di­ent Descent Based, and the Embed­ding Approach on Four Pub­lished Hybrid Opti­mal Con­trol Examples

    “…Com­mon mis­con­cep­tions regard­ing the embed­ding approach are addressed includ­ing whether or not it results in an aver­age value con­trol model (no), is nec­es­sary to “tweak” the algo­rithm to get bang-​​bang solu­tions (no), requires infi­nite switch­ing (no), has real-​​time capa­bil­ity (yes), or reduc­tion to a clas­si­cal non­lin­ear opti­miza­tion prob­lem (a desir­able yes).”

    control-​​theory operations-​​research algo­rithms numerical-​​methods philosophy-​​of-​​engineering design-​​patterns nudge-​​targets

  • [1203.3270] Extrac­tion of Facial Fea­ture Points Using Cumu­la­tive Histogram

    “This paper pro­poses a novel adap­tive algo­rithm to extract facial fea­ture points auto­mat­i­cally such as eye­brows cor­ners, eyes cor­ners, nos­trils, nose tip, and mouth cor­ners in frontal view faces, which is based on cumu­la­tive his­togram approach by vary­ing dif­fer­ent thresh­old val­ues. At first, the method adopts the Viola-​​Jones face detec­tor to detect the loca­tion of face and also crops the face region in an image. From the con­cept of the human face struc­ture, the six rel­e­vant regions such as right eye­brow, left eye­brow, right eye, left eye, nose, and mouth areas are cropped in a face image. Then the his­togram of each cropped rel­e­vant region is com­puted and its cumu­la­tive his­togram value is employed by vary­ing dif­fer­ent thresh­old val­ues to cre­ate a new fil­ter­ing image in an adap­tive way. The con­nected com­po­nent of inter­ested area for each rel­e­vant fil­ter­ing image is indi­cated our respec­tive fea­ture region. A sim­ple lin­ear search algo­rithm for eye­brows, eyes and mouth fil­ter­ing images and con­tour algo­rithm for nose fil­ter­ing image are applied to extract our desired cor­ner points auto­mat­i­cally. The method was tested on a large BioID frontal face data­base in dif­fer­ent illu­mi­na­tions, expres­sions and light­ing con­di­tions and the exper­i­men­tal results have achieved aver­age suc­cess rates of 95.27%.”

    image-​​segmentation image-​​analysis face-​​recognition algo­rithms nudge-​​targets

  • [1203.3284] Effi­cient Enu­mer­a­tion of the Directed Binary Per­fect Phy­lo­ge­nies from Incom­plete Data

    “We study a character-​​based phy­logeny recon­struc­tion prob­lem when an incom­plete set of data is given. More specif­i­cally, we con­sider the sit­u­a­tion under the directed per­fect phy­logeny assump­tion with binary char­ac­ters in which for some species the states of some char­ac­ters are miss­ing. Our main object is to give an effi­cient algo­rithm to enu­mer­ate (or list) all per­fect phy­lo­ge­nies that can be obtained when the miss­ing entries are com­pleted. While a sim­ple branch-​​and-​​bound algo­rithm (B&B) shows a the­o­ret­i­cally good per­for­mance, we pro­pose another approach based on a zero-​​suppressed binary deci­sion dia­gram (ZDD). Exper­i­men­tal results on ran­domly gen­er­ated data exhibit that the ZDD approach out­per­forms B&B. We also prove that count­ing the num­ber of phy­lo­ge­netic trees con­sis­tent with a given data is #P-​​complete, thus pro­vid­ing an evi­dence that an effi­cient ran­dom sam­pling seems hard.”

    phy­lo­ge­net­ics inverse-​​problems genet­ics algo­rithms sta­tis­tics nudge-​​targets

  • [1203.0879] Design­ing and using prior knowl­edge for phase retrieval

    “In this work we develop an algo­rithm for sig­nal recon­struc­tion from the mag­ni­tude of its Fourier trans­form in a sit­u­a­tion where some (non-​​zero) parts of the sought sig­nal are known. Although our method does not assume that the known part com­prises the bound­ary of the sought sig­nal, this is often the case in microscopy: a spec­i­men is placed inside a known mask, which can be thought of as a known light source that sur­rounds the unknown sig­nal. There­fore, in the past, sev­eral algo­rithms were sug­gested that solve the phase retrieval prob­lem assum­ing known bound­ary val­ues. Unlike our method, these meth­ods do rely on the fact that the known part is on the bound­ary. Besides the recon­struc­tion method we give an expla­na­tion of the phe­nom­ena observed in pre­vi­ous work: the recon­struc­tion is much faster when there is more energy con­cen­trated in the known part. Quite sur­pris­ingly, this can be explained using our pre­vi­ous results on phase retrieval with approx­i­mately known Fourier phase.”

    image-​​analysis image-​​processing learn­ing inverse-​​problems algo­rithms nudge-​​targets

  • [1203.3415] A New Approach to Count Pat­tern Motifs Using Com­bi­na­to­r­ial Techniches

    “We pro­posed two new exact algo­rithms to detect net­work motifs of size 3 and 4. Con­sid­er­ing that motifs need to count the iso­mor­phic pat­terns in the orig­i­nal graph $G(V,E)$ and in a set of ran­dom­ized graphs, the fol­low­ing com­plex­i­ties con­cern about count iso­mor­phic pat­terns in a sin­gle graph. Let $m=|E|$ and let $a(G)$ be the arboric­ity of $G$. Assume $|E|geq|V|$. We describe a $O(a(G)m)$ time com­plex­ity algo­rithm to count iso­mor­phic pat­terns of size 3. The com­plex­ity is a $O({msqrt{m}})$ in the worst graph. The sec­ond algo­rithm is a $O(m^2)$ com­plex­ity algo­rithm to count iso­mor­phic pat­terns of size 4. The final result was expres­sive faster when com­pared with other imple­mented algorithms.”

    network-​​theory graph-​​theory algo­rithms nudge-​​targets

Items of some interest…

Posted on by

These are my recent Pin​board​.in links:

  • Sell­ing the Idea of a Chris­t­ian Nation: David Barton’s Alter­nate Intel­lec­tual Uni­verse | Pol­i­tics | Reli­gion Dispatches

    “I use the term “debate” in quotes because it is fraud­u­lent. Even advo­cates of the view­point of the “god­less Con­sti­tu­tion” (such as his­to­ri­ans Isaac Kram­nick and R. Lau­rence Moore) fully under­stand the reli­gious base of Amer­i­can his­tory. They sug­gest sim­ply (as Jon Stew­art was try­ing to get at) that the framers rather delib­er­ately excluded reli­gion, not because they sought an exclu­sion of reli­gion from the pub­lic square, but sim­ply to avoid any spe­cial priv­i­leges for it at the fed­eral level. Even­tu­ally, those views were incor­po­rated into state laws through the 14th Amend­ment, through the plu­ral­iza­tion of Amer­i­can life in the twen­ti­eth cen­tury, and through the epochal court cases of the 1940s through the 1970s. The Chris­t­ian Nation “debate” is not really an intel­lec­tual con­test between legit­i­mate con­tend­ing view­points. Instead, it is a man­u­fac­tured “con­tro­versy” akin to the global warm­ing “debate.” On one side are pur­vey­ors of a rich and com­plex view of the past, includ­ing most his­to­ri­ans who have writ­ten and debated fiercely about the found­ing era. The “other side” is a group of ide­o­log­i­cal entre­pre­neurs who have cre­ated an alter­nate intel­lec­tual uni­verse based on a his­tor­i­cal fun­da­men­tal­ism. In their drive to cre­ate a usable past, they show lit­tle respect for the past as a for­eign country. ”

    Chris­tian­ity con­ser­vatism history-​​is-​​a-​​feature-​​not-​​a-​​bug sto­ry­telling

  • Poor Mojo’s Newswire: Twit­pic qui­etly changes Terms of Ser­vice, they can now sell any pic you upload

    “You retain all own­er­ship rights to Con­tent uploaded to Twit­pic. How­ever, by sub­mit­ting Con­tent to Twit­pic, you hereby grant Twit­pic a world­wide, non-​​exclusive, royalty-​​free, sub­li­censeable and trans­fer­able license to use, repro­duce, dis­trib­ute, pre­pare deriv­a­tive works of, dis­play, and per­form the Con­tent in con­nec­tion with the Ser­vice and Twitpic’s (and its suc­ces­sors’ and affil­i­ates’) busi­ness, includ­ing with­out lim­i­ta­tion for pro­mot­ing and redis­trib­ut­ing part or all of the Ser­vice (and deriv­a­tive works thereof) in any media for­mats and through any media channels.”

    Twit­ter intellectual-​​property EULA licens­ing

  • Trade Secrets and Pub­lished Patent Appli­ca­tions — Patent Law Blog (Patently-​​O)

    “Patent Pub­li­ca­tion Elim­i­nates Trade Secret: In a straight­for­ward opin­ion, the appel­late panel held once pub­lished, the infor­ma­tion in a patent appli­ca­tion should be con­sid­ered “gen­er­ally known and read­ily avail­able” and there­fore are no longer amenable to trade secret protection.  ”

    patents intellectual-​​property lawyers nondis­clo­sure

Items of some interest…

Posted on by

These are my recent Pin​board​.in links:

  • Accor­dion Mini Books | WHCC

    “Accor­dion Mini Books are the per­fect gift item for your clients to use as mini folios and brag books. Avail­able in a wal­let and a square 3×3 size, order an Accor­dion Mini Book on any of our press printed papers – stan­dard semi-​​gloss, art linen, art water­color, art recy­cled, and pearl. UV coat­ing can also be added. Cover options include fab­rics, leathers, suedes, or a per­son­al­ized cus­tom photo cover in lus­tre or metal­lic with a matte lam­i­nate. The wal­let Accor­dion Mini Books have up to 14 cus­tomiz­able pan­els and the square 3×3 has up to 10 cus­tomiz­able pan­els. This is a great add-​​on item with any order! Accor­dion Mini Books are avail­able through ROES with a min­i­mum order of 3 iden­ti­cal books, order each side as a spread. Frosted Slip Cov­ers are also avail­able for only $1/​book.”

    • book-​​art project swag-​​making

  • The Truth About the Con­fed­er­acy | Corrente

    “One thing I really would like you to take away from this diary is a basic sense of how the United States, as a self-​​governing demo­c­ra­tic repub­lic, can­not long tol­er­ate oli­garchic and aris­to­cratic ideas in its body politic. This is becom­ing an increas­ingly urgent issue for us today, because the Amer­i­can con­ser­v­a­tive move­ment today is basi­cally a replica of the slavery-​​defending, anti-​​free labor, government-​​hating, insur­rec­tion minded, treason-​​breathing, vio­lently inclined Con­fed­er­acy. And, I want you to be able to instantly rec­og­nize and rebut the false his­to­ries that neo-​​Confederates have cre­ated. So, the first mate­r­ial I place before you is an excerpt from an impor­tant and emo­tion­ally pow­er­ful 1995 book, What They Fought For, 1861–1865, a mas­ter­ful sur­vey and sum­mary of pri­vate cor­re­spon­dence from Civil War sol­diers and offi­cers, by James M. McPherson.”

    • Civil-​​War that-​​Santayana-​​quote-​​you-​​know-​​the-​​one con­ser­vatism Bushism his­tory cultural-​​assumptions

  • mojombo/​grit — GitHub

    “Grit gives you object ori­ented read/​write access to Git repos­i­to­ries via Ruby. The main goals are sta­bil­ity and per­for­mance. To this end, some of the inter­ac­tions with Git repos­i­to­ries are done by shelling out to the system’s git com­mand, and other inter­ac­tions are done with pure Ruby reim­ple­men­ta­tions of core Git func­tion­al­ity. This choice, how­ever, is trans­par­ent to end users, and you need not know which method is being used.”

    • version-​​control Ruby git GitHub library pro­gram­ming doc­u­ments

  • Economist’s View: Labor Mar­ket Pol­icy in the Great Recession

    “The pos­i­tive les­son for the US is that we have a lot of scope to give employ­ers incen­tives to cut hours rather than jobs, includ­ing improv­ing and expand­ing “work-​​sharing” (part-​​time unem­ploy­ment ben­e­fit) pro­grams as well as imple­ment­ing new direct tax cred­its to firms that expand paid time off (paid sick days, paid fam­ily leave, paid vaca­tions, and other mea­sures). The neg­a­tive les­son is that focus­ing on supply-​​side issues such as train­ing, edu­ca­tion, and improved job-​​matching for the unem­ployed –as much sense as they make in the long run– is not likely to get us very far when the econ­omy is at 9 per­cent unem­ploy­ment. Den­mark does far more than we could ever hope to accom­plish along these lines and the unem­ploy­ment there almost dou­bled between 2007 and 2010.”

    • unem­ploy­ment public-​​policy economic-​​crisis gov­ern­ment history-​​is-​​a-​​feature-​​not-​​a-​​bug

  • The per­ils of filter-​​then-​​publish

    “When I pri­vately asked them why they had used R*-trees, while it was easy to check exper­i­men­tally that they did not help, the answer was “it was the only way to get our paper in a major con­fer­ence”. So my work has been made more com­pli­cated for the sole pur­pose of impress­ing the review­ers: “look, I know about R*-trees too!””

    • peer-​​review cultural-​​dynamics pub­lish­ing academic-​​culture jour­nals disintermediation-​​in-​​action

  • Why Do We Quote? The Cul­ture and His­tory of Quo­ta­tion — Open Book Publishers

    “This is a rich and engag­ing work of out­stand­ing schol­ar­ship. Schol­ars in soci­olin­guis­tics, lit­er­a­ture, and folk­lore will rec­og­nize the impor­tance of the book for their fields. Gen­eral read­ers will find it just plain interesting”

    • academic-​​culture books want

  • They Never Cared About Unem­ploy­ment « Open Economics

    “What’s strik­ing, though, is that even in Jan­u­ary of 2010, when unem­ploy­ment was over 10%, deficits received equal men­tion as unem­ploy­ment. The media is cer­tainly cul­pa­ble here, but I’m guess­ing that their head­lines are dri­ven by the polit­i­cal dis­cus­sion, which since the pas­sage of the stim­u­lus has been entirely warped. Goes to show that our polit­i­cal lead­ers, and the media by exten­sion, will never give unem­ploy­ment the atten­tion it deserves.”

    • economic-​​crisis financial-​​crisis pol­i­tics unem­ploy­ment bankers-​​should-​​start-​​avoiding-​​lampposts-​​right-​​about-​​now

  • Guest Post: Gei­th­ner Says “The Size Of The Shock Was Larger Than What Pre­cip­i­tated The Great Depres­sion” « naked capitalism

    “…(So the shock was even big­ger than the one lead­ing up to the Depres­sion because Gei­th­ner and his bud­dies helped blow the bub­ble and try to cover up wrong­do­ing on Wall Street.) Gei­th­ner has been equally bad as Trea­sury boss. Indeed, there is hardly a sin­gle inde­pen­dent econ­o­mist who thinks he has been respond­ing appro­pri­ately to the eco­nomic cri­sis. Sorry to say, but Gei­th­ner has long been a yes-​​man to the powers-​​that-​​be, who ships pal­lets of money wher­ever he is told with­out ques­tion or any follow-​​up or track­ing what­so­ever. Even worse, Gei­th­ner has been called an idiot by Nas­sim Taleb and a “con man” by Time Mag­a­zine. No won­der we’re going to even­tu­ally have another crash … And because Gei­th­ner (along with Bernanke) have insisted that the big banks be bailed out at Main Street’s expense, that the sta­tus quo be pro­tected instead of reformed, and that the U.S. insure the debts of the too big to fails, the next cri­sis will be even big­ger than the last.”

    • bankers-​​should-​​start-​​avoiding-​​lampposts-​​right-​​about-​​now financial-​​crisis this-​​will-​​end-​​badly

  • Stuff Dig­i­tal Human­ists Like: Defin­ing Dig­i­tal Human­i­ties by its Values

    “Here are five to start us off: Like: Twit­ter /​ Don’t like: Face­book. The first thing we have to men­tion, which we have men­tioned a few times already, is Twit­ter. The rea­sons we like Twit­ter are com­plex and I won’t pre­tend to under­stand them all, but I’ll throw out a few sug­ges­tions. First, its “fol­low” rather than “friend” model is more open, allows for the col­lab­o­ra­tion and non-​​hierarchy that the Inter­net and dig­i­tal human­i­ties val­ues. Sec­ond, and related to this, Twit­ter is the place where content-creators—journalists, writ­ers, artists, web devel­op­ers, etc.—tend to hang out. We over­lap with those com­mu­ni­ties, or at least seek to over­lap with them, in pro­duc­tive ways. They are the dis­tant nodes from which we hope new inno­va­tions will come. Third, Twit­ter, in the way we use it, is mostly about shar­ing ideas whereas Face­book is about shar­ing rela­tion­ships. Schol­ars are good at ideas, maybe less so at rela­tion­ships. Like: Agile devel­op­ment /​ Dis­like: long plan­ning cycles. The sec­ond thing I’ll men­tion is agile devel­op­ment, the phi­los­o­phy of “releas­ing early and often,” which we do not only with software/​code but also with our ideas and writ­ing when we Tweet, blog, and chat. We do this as good neigh­bors but also in the hope that releas­ing our code and ideas will improve with con­tri­bu­tions from end points of our net­works. Like: DIY /​ Dis­like: Out­sourc­ing. Most of the most suc­cess­ful dig­i­tal human­i­ties projects are those done by scholar/​technologists not those imag­ined by schol­ars and imple­mented by tech­nol­o­gists. Like­wise, the most suc­cess­ful dig­i­tal human­ists are schol­ars who know the tech­nol­ogy, often those who are self-​​taught, not ones who seek a client-​​vendor rela­tion­ship with tech­nol­o­gists. We take this insight to heart in our hir­ing at CHNM, look­ing for peo­ple with for­mal train­ing in the human­i­ties and self-​​taught tech skills. Like: PHP /​ Dis­like: C++. Fourth, and fol­low­ing from the last point, we like PHP not C++. This is another way of say­ing we like the trans­par­ent, easy-​​to-​​learn, and sim­ple (if some­times ham-​​handed) tech­nolo­gies of the Web more than the more pow­er­ful, more sophis­ti­cated, more ele­gant, but less approach­able com­piled code of the desk­top. A focus on get­ting the most out of sim­ple, trans­par­ent, ver­nac­u­lar tech­nolo­gies allows us to keep the door to the field open to new entrants. Like: Extra­mural fund­ing /​ Dis­like: Intra­mural fund­ing. In one respect, this may seem obvi­ous: every­body likes grants. In another respect it’s prob­a­bly going a lit­tle too far to say we don’t like intra­mural fund­ing: it is essen­tial to build­ing and main­tain­ing capac­ity for our cen­ters and staff. But it seems to me the most suc­cess­ful dig­i­tal human­i­ties projects are those that result from com­pet­i­tive grant mak­ing processes, espe­cially the fed­eral grant mak­ing process. Why is this? I can point to at least three rea­sons: 1) Attract­ing grant money keeps us inno­vat­ing, which, like it or not, is a pre­mium in our busi­ness. Grants are given for new work, not for more of the same. 2) Writ­ing grants and serv­ing on pan­els keep us in con­ver­sa­tion with the field. We have to keep cur­rent and keep in touch with one another to jus­tify our projects to grant­mak­ers and to rec­om­mend oth­ers’ projects for fund­ing. Increas­ingly, fund­ing guide­lines them­selves require col­lab­o­ra­tion. 3) Unlike much tra­di­tional schol­ar­ship, which often requires one big deliv­er­able (a book) after years of close-​​kept study, research, and writ­ing, grant work requires defin­ing and meet­ing a set of closely timed, con­crete deliv­er­ables, a mode of work which encour­ages the kind of agile devel­op­ment so val­ued by the Inter­net and dig­i­tal human­i­ties community.”

    • digital-​​humanities cultural-​​norms open-​​access open­ness network-​​culture

  • Agilistry Stu­dio — Agile Management

    “Sev­eral stud­ies indi­cate that “old-​​style” man­agers are the biggest obsta­cle in tran­si­tions to Agile soft­ware devel­op­ment. Devel­op­ment man­agers and team lead­ers need to learn what their new role is in Agile soft­ware devel­op­ment orga­ni­za­tions. This course will help them.”

    • man­age­ment agile-​​management project-​​management class Jurgen-​​Appelo

  • Embed­ding Col­lab­o­ra­tion from the Start — Jimmy Guter­man — Our Edi­tors — Har­vard Busi­ness Review

    “At Nokia, infor­mal men­tor­ing begins as soon as some­one steps into a new job. Typ­i­cally, within a few days, the employee’s man­ager will sit down and list all the peo­ple in the orga­ni­za­tion, no mat­ter in what loca­tion, it would be use­ful for the employee to meet. This is a deeply ingrained cul­tural norm, which prob­a­bly orig­i­nated when Nokia was a smaller and sim­pler orga­ni­za­tion. The man­ager sits with the new­comer, just as her man­ager sat with her when she joined, and reviews what top­ics the new­comer should dis­cuss with each per­son on the list and why estab­lish­ing a rela­tion­ship with him or her is impor­tant. It is then stan­dard for the new­comer to actively set up meet­ings with the peo­ple on the list, even when it means trav­el­ing to other loca­tions. The gift of time — in the form of hours spent on coach­ing and build­ing net­works — is seen as cru­cial to the col­lab­o­ra­tive cul­ture at Nokia.”

    • col­lab­o­ra­tion man­age­ment Workantile-​​ideas social-​​norms social-​​networks organizational-​​design

  • The Con­ver­sa­tion, the startup Aus­tralian news site, wants to bring aca­d­e­mic exper­tise to break­ing news » Nie­man Jour­nal­ism Lab » Push­ing to the Future of Journalism

    “First, “every author has to fill out a pro­file, so the reader knows who the per­son is and their edu­ca­tion. And there is the addi­tional require­ment of a dis­clo­sure of any poten­tial con­flicts which might color their judgment.” Second, in response to the polit­i­cal ques­tion — after not­ing that my academics-​​are-​​liberal asser­tion might be a bit loaded — Jas­pan replied that what The Con­ver­sa­tion is ulti­mately doing is putting peo­ple in touch with “aca­d­e­mics who are usu­ally bet­ter informed than the gen­eral pub­lic because of their depth of knowl­edge and their sense of the com­plex­ity of the issue.” Third, and most impor­tant, Jas­pan sees The Con­ver­sa­tion, true to its name, as lead­ing to pub­lic debate. “One of the key things we want to do with a public-​​facing media chan­nel is to make sure we have a range of views on some­thing like the exe­cu­tion of Osama Bin Ladin, and that we have dif­fer­ent inter­pre­ta­tions of what hap­pened and whether or not the means in which it was done were judi­cial.” The main goal, though: “We want to sur­prise our read­ers. We don’t want to give them the usual expla­na­tions, alter­na­tive insights, and view­points — and that will lead to lively con­ver­sa­tion.” Jaspan’s back­ers come from both the non­profit and for-​​profit realms. The Con­ver­sa­tion is backed by Ernst & Young, among other cor­po­rate supporters. And from acad­e­mia, he has drawn on some of the top Aus­tralian research uni­ver­si­ties, in addi­tion to Australia’s Depart­ment of Education. To find the aca­d­e­mics, Jas­pan and his staff did a “cen­sus” of aca­d­e­mics based on their areas of exper­tise. Then, by word of mouth, they asked par­tic­i­pat­ing aca­d­e­mics to rec­om­mend col­leagues who would make good con­trib­u­tors to the site.”

    • jour­nal­ism acad­e­mia com­men­tary deepening-​​the-​​news exper­i­ment con­ver­sa­tion

  • Cen­sored Genius: The Fight Goes On.

    “A recent post by Seth Godin attempts to define a librar­ian as some­thing lim­ited by for­mat: print books are bad, dig­i­tal bits are good. So librar­i­ans should become dig­i­tal wiz­ards, or some­thing. I think the cur­rent hip term is “data sherpa who directs and engages con­ver­sa­tions,” or some other bull­shit. And a librar­ian is bad if she’s not con­tin­u­ously evolv­ing and grow­ing toes. But a good librar­ian would never exclude a data for­mat from the search results. You ask me for infor­ma­tion on tur­tles and you’re get­ting every­thing I can find, and that includes printed books. But chances are, you’re going to wave your Kin­dle in my face and say, “I want it here.” And regard­less of my reply, my eyes will tell you to go fuck your­self. Sixty per­cent of the world’s peo­ple would kill to have a library filled with books. Some coun­tries won’t even let you into a library with­out proper iden­ti­fi­ca­tion. But Amer­i­cans, on our rapid decent from being a world power toward become the world’s bag boy, have lost sight of what has last­ing value and moved on to what has recur­ring monthly fees. In response to Seth’s Blog, Bobbi New­man says, “One of the many roles of the pub­lic library is to ensure that all peo­ple have access to that infor­ma­tion.“ And that is the fun­da­men­tal dif­fer­ence with every cur­rent view of the library and the real pur­pose of the library: Libraries are for everyone.”

    • librar­i­ans libraries library2.x cultural-​​assumptions archives cultural-​​banking-​​vs-​​cultural-​​levelling

  • Pirate Bay Heads Nor­we­gian Domain Block­ing List | TorrentFreak

    “The spread of anti-​​filesharing mea­sures across the United States and Europe appears to be accel­er­at­ing at a some­what dizzy­ing pace. On an almost daily basis dur­ing the last few months sto­ries about con­tro­ver­sial and some­times dra­con­ian mea­sures to deal with online infringe­ment have hit the head­lines. Say what you like about the big movie and music stu­dios – they cer­tainly know how to coor­di­nate their lob­by­ing to per­fec­tion. Tim­ing like this, with leg­is­la­tion being mulled in many major mar­kets simul­ta­ne­ously, sends a pow­er­ful message.”

    • rein­ter­me­di­a­tion law glob­al­ism copyright-​​war that-whole-free-assembly-thing-depends-on-what-you’re-up-to