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The new quantitative revolution Dialogues in Human Geography-2014-Wyly-26-38

The new quantitative revolution Dialogues in Human Geography-2014-Wyly-26-38
The new quantitative revolution Dialogues in Human Geography-2014-Wyly-26-38

Commentary

The new quantitative revolution Elvin Wyly

University of British Columbia,Canada

Every time you go to https://www.wendangku.net/doc/8915918987.html,,you are the

subject of a randomized experiment.Every time you search on Google,you are the subject of an experiment.Why not every time a student here does something?

Gary King(quoted in Heller,2013:85) The structure,the geometry,of the intellectual space called geography has changed and sharply increased

in multidimensionality.

Peter Gould(1979:145) The ferment of ideas was fierce;hypotheses were tested,paradigms traded,models proposed,theories suggested,explanations offered,systems simulated, and laws sorely sought after...reality was ransacked

in search of theory.

Neil Smith(1979:356) In‘Spatial Science and Quantitative Analysis in Geographical Curricula’,Johnston et al.(2014) re place geography’s‘quantitative revolution’.This replacement entails a reevaluation of the place occupied by the revolution in the discipline’s his-tory,and a reconsideration of the current position of the revolution’s methods in higher education curricula.Responding to a critical social theory tra-dition in human geography that was refined through opposition to a particular strain of‘geography in its quantitative and positivist guise that emerged in the1960s’(Cresswell,2013:281),Johnston et al.analyze the pervasive misrepresentations of quantitative analysis that undermine the coherence of human geography as well as its role‘in the formation of an informed citizenry in data-driven, evidence-based policy societies’(2014:4).Our curricula and our disciplinary histories,Johnston et al.tell us,have left us with a deceptive caricature inherited from the past—a regime of quantitative spatial science premised on‘view from nowhere’mechanistic models of homo economicus that ignored the deeply contextual contingencies of human behavior.Contemporary spatial science, Johnston et al.argue(p.6),actually‘emphasises similar general arguments to those applied by scho-lars in the discipline’s“social theory”compart-ments’.Developments in public policy,analytical technologies,and massive flows of‘big data’now enable new ways to transcend the‘quantitative versus qualitative’divide,Johnston et al.suggest, presenting us with unprecedented opportunities and obligations.Contemporary spatial science—‘as currently practiced and not as pioneered50 years ago’—merits a place as‘a core component of all undergraduate degree curricula and a key resource on which all postgraduates draw’(p.17).

Johnston et al.have given us an extraordinary contribution.This is a panoramic survey of the legacy of half a century of innovation in spatial science—put into a critical,constructive Corresponding author:

Elyvyn Wyly,University of British Columbia,Vancouver,BC V6T 1Z4,Canada.

Email:elvin.wyly@geog.ubc.ca

Dialogues in Human Geography

2014,Vol.4(1)26–38

aThe Author(s)2014

Reprints and permission:

https://www.wendangku.net/doc/8915918987.html,/journalsPermissions.nav

DOI:10.1177/2043820614525732

https://www.wendangku.net/doc/8915918987.html,

engagement with half a century of innovation in critical social theory.Their‘case(plea?)’that the choice to study quantitative spatial science‘should not be denied students’(p.17)presents a focal point for curriculum struggles in an era of over-whelming institutional and technological change.

I concur with nearly all of Johnston et al.’s inter-pretations and recommendations,although I must emphasize that I am thoroughly unqualified to advise on curriculum standards for an educational system in which the audit culture is quickly destroying the conditions of possibility for uncom-modified free thought and independent scholarly knowledge production.(It is in your rational self-interest to stop reading,because‘reading’counts for nothing on your periodic performance assess-ment,and unless you are cited,these words will contribute nothing to your H-index.)

Nevertheless,I have a responsibility to offer something beyond a passive‘I agree!’in response to Johnston et al.’s serious,important call.More-over,simple agreement runs the risk of reinforcing the very quantitative/qualitative divide Johnston et al.rightly question.In the all-administrative uni-versity(Ginsberg,2011)where an audit culture legitimated as productivity measurement has evolved into a Parsonian structural–functionalist content creation infrastructure,the opportunity costs of time and attention mean that any endorse-ment of quantitative methods,spatial science,and GIScience as core components‘of all undergradu-ate degree curricula’(Johnston et al.,2014:17) will be perceived as denigration or disinvestment from their methodological others—the kaleido-scope of humanistic,literary,interpretive,ethno-graphic,and other qualitative approaches.I am torn apart by such choices,and if you’re reading these words you are too—because the essence of any dialo-gue in human geography is a pluralist spirit of‘both/ and’engagement that builds alliances as far as possi-ble until we are forced into the contentious choices of ‘either/or’(Barnes,2009).As an alternative,there-fore,I’ll offer a cautionary note based on the broader context of the important curricular principles advanced by Johnston et al.Contemporary political economy and the mobilization of powerful institu-tions seeking to transform the role of education in society are driving a new‘quantitative revolution’. The revolution is advancing most rapidly in those political circumstances where elite coalitions have been most successful in using the friendly language of‘evidence-based policy’to conceal the true emphasis on policy-driven evidence manufacturing(Slater,2009).After40years of neoliberalization and commodification has trans-formed‘policy’into the more sophisticated eva-sions of‘governance’,the co-optation is now entering a quickening phase of consolidated auto-mation.New curricula for spatial science and quantitative analysis are being written in code, enmeshed in the application programming inter-faces of neoliberal digital capitalism.As big data neoliberalism and‘cognitive–cultural capitalism’(Scott,2011a,2011b)transform education,you, me,and every other human geographer suddenly find ourselves on the wrong side of the River Alpheus in an automated reenactment of geogra-phy’s Augean Period(Gould,1979). Contextualizing spatial science Johnston et al.’s manifesto is at once a richly detailed historiography of geography’s quantita-tive revolution and a contemporary pedagogical proposal of brutal simplicity.The logic is compel-ling:Disciplinary fragmentation has given rise to misrepresentation of the history of spatial science, obscuring the contemporary possibilities of quanti-tative geographies informed by critical social the-ory to engage wider publics of‘an informed citizenry’in‘data-driven,evidence-based policy societies’(p.4).Yet Johnston et al.achieve this compelling coherence through a relentless focus on the pure,inherent scholarly merits of the quan-titative curriculum.This is a work written by geo-graphical scholars for an audience of scholarly geographers on the assumption that scholars retain authority over the content of the curriculum. Unfortunately,this important scholarly conversa-tion takes place within a broader context of devas-tating coercive restructuring of education in conformance with the imperatives of short-term, unstable waves of innovative commodification as education is transformed into just another

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‘knowledge industry’(Scott,2011a,2011b).The infusion of competitive market metrics,techno-cratic instrumental rationality,and neoliberal axioms of consumer choice are transforming edu-cation at an accelerating pace.One of the central elements of the neoliberalization of knowledge production involves‘a ubiquitous quantification of every aspect of teaching,research,and service’and‘the forced crunching of all intellectual activity into a number’(Smith,2010).

Geography has become means and ends in this curricular creative destruction.Three dimensions of the new quantitative revolution merit caution as we consider how to implement Johnston et al.’s rec-ommendations.The first aspect is the overwhelming magnitude of new data worlds;the second is the rise of mobile data;and the third is the intensified deployment of quantification on the enterprise of geographic education itself.

Geographies of big data

The new revolution involves qualitative transforma-tions of quantitative data.The sheer volume of new sources of data,and the growth rate of data produc-tion and distribution,merits new superlatives every year,every month.Accelerating velocity has begot-ten simultaneous shifts in the production relations of data,as an evolving galaxy of corporations and screen-scraping bots creates what the science histor-ian George Dyson(2012)calls‘a universe of self-replicating code’;Dyson estimates the current growth rate at5trillion bits per second.The total volume of global stored information is growing four times faster than the world economy,and digital processing speeds are advancing nine times faster (Mayer-Scho¨nberger and Cukier,2013:9).In one sense,Johnston et al.’s contribution is a clarion call for geographical expertise:Every professional geo-grapher can instantly recognize the desperate socie-tal need for careful,critical appreciation of the distinctive essence of spatial data,the art and sci-ence of cartographic communication,and the infer-ential challenges of spatial analysis.There’s an exciting,tantalizing market opportunity here—a chance for geographers to shape the emerging era of‘computational social science’(King,2009),to map the imaginative and performative landscapes of‘hacker cartography’(McConchie,2014)and newly geocoded social and economic landscapes (Walker,2013),and to analyze the rapidly evolving spatialities of human communication in a socially networked world(Crampton et al.,2012;Shelton et al.,2012).Johnston et al.’s curriculum could help us prepare a generation of students for life in this new world of ubiquitous big data,as more and more of it becomes explicitly spatial data.

Yet the new lifeworlds of data are not without risk.They can be ruthlessly ahistorical—despite the best efforts of projects like the National Histor-ical geographic information system(MPC;Minne-sota Population Center,2011)and other new ‘digital imaginations’(Offen,2013)across the humanities—in ways that mortgage the attention premium of‘now’.Big data give us a quickly expanding,shallow view of the vast horizontal landscape of the desert of the present real,with each new technological advance accomplishing new kinds of devalorization of past generations of human knowledge.The speedy exponential cas-cade of today’s digital vivisection of events large and small yields infinitely changing measures of attention and impact,as in the current enthusiasm for Klout scores and global speeds measured as tweets per minute;anything from the past that can-not be digitized,or that is disallowed from index-ing on a server’s robots.txt file,becomes another Anaximander fragment.And in the attention econ-omy of the present,inflationary pressures con-stantly ratchet up the expectations of audiences. Policy elites,students,and other‘consumers’are overwhelmed with data,necessitating new learning cultures that alternate between adaptive cynicism and voracious demands for new interactive visualization experiences to make sense of all the data.Experience and cynicism,moreover,are increasingly privatized and dehumanized in the ecosystems of corporate competition.The social–theoretical challenges to geography’s quan-titative revolution during the crucial period between1957and1977(Gould,1979)were fought by human geographers on the terrain of a methodo-logical positivism that portrayed data as a means of finding common ground—embodied most clearly

28Dialogues in Human Geography4(1)

in analysts’use of data from the public,govern-mental population census(Shearmur,2009;Stein-metz,2005).As capitalists and the political Right have learned to hijack postpositivist poststructural-ism,however,many of the nonmilitary public-sector data systems refined in the era of the Keyne-sian welfare state are being undermined or destroyed,while vast networks of proprietary cor-porate digital dossiers enable truly revolutionary transformations in the nature of observation. Indeed,in those parts of the world shaped by the most advanced developments in the evolutionary trajectories of neoliberalization,it is almost impos-sible to distinguish‘public’data by the criterion of public,democratic control over content,produc-tion,and usage.The data politics of partially auto-mated‘Siren Servers’(Lanier,2013)of Google, Facebook,and Twitter have supplanted the policy debates of the governmental census of Fordist methodological positivism(Steinmetz,2005).

Strange new hybrids are emerging.Silicon Valley innovation,venture-capital investment and Wall Street financialization,and digital transforma-tions of circuits of production and consumption have been consolidated in the‘new frontiers of capi-talist expansion’(Scott,2011a:846,848),driven by‘the far-reaching mobilization of the mental and behavioral powers’of workers and consumers. While much of this mobilization involves the agency and conscious creativity of‘knowledge work’,the advocates of big data are far more inter-ested in new kinds of observation.Some of the new possibilities come from the massive scale effects of the digitization of long-established flows of infor-mation.Some are derived from new abilities to observe what people do rather than what they say they do in surveys(this is a revival of the‘revealed preference analysis’from geography’s behavioral revolution in the1970s).And a growing share are synthetic representations created through new kinds of aggregation,linkage,and sociospatial or behavioral inference.More of these new data streams are explicitly dynamic and readily inte-grated into infrastructures designed for automated collection,processing,and further informational synthesis.Data are producing data,and corporate algorithms are producing corporate algorithms:This is the self-replicating code that looks so new in prac-tice but so familiar in theories across centuries of human history(Dyson,1997).Now it’s something that you and I experience every day,because even the once-obscure corners of scholarly human geogra-phical knowledge production—the textual content of journal articles,the correspondence accumulated through peer review processes,the page views of reading and scholarly citations—are deeply embedded into corporate data systems and algorith-mic analysis(Schuurman,2013).If you’re reading these words via any digital device,there’s a scattered patchwork of clickstream data on the path that led you here,consisting of innumerable data points on your digital reading history,my digital authorship history,and our shared correlations with an unknown number of other transactions among‘digital individ-uals’in this evolving world of sociospatial data (Curry,1997;Lanier,2010,2013).Given the velocity differential between algorithmic bots and human reading,humans will account for a very small pro-portion of the‘views’of this textual content and the differential will grow exponentially over time. Mobilization and mapping

The second dimension of the new quantitative revo-lution involves a process best understood as data mobilization:The simultaneous acceleration of(a) the circulation of data among individuals and insti-tutions in place wherever they happen to be and(b) the production of data streams representing humans in motion.This trend is most vivid in the smart-phone/app economy,where real-time locational data have quickly become the fuel for competitive innovation in an emerging fusion of global position-ing system–enabled hardware,locationally dynamic software,and the embodied,place-bound experi-ences of consumers in motion in their daily lives. Facebook’s relations with advertisers and investors are illustrative.With a monthly active user base just over1.1billion worldwide and an average daily user online duration of34min,Facebook’s servers han-dle a data stream of34.9billion min of human social relations each day.In one parallax view,this torrent of data can be viewed simply as a Kantian temporal distortion:each day,Facebook is given more than

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64,000years of human expression in a digital form readily suited for advanced analyses that exceed the wildest mathematical hypotheticals of the quantita-tive revolutionaries of the1950s:Berry’s(1958) pedagogical notes on numerical taxonomy are embedded in the code Wolfram(2013)deploys to classify millions of Facebook friend networks.Yet Wall Street investors have another perspective on the global desktop-to-smartphone tectonics and have been pressuring Facebook ever since the firm’s May2012epic-fail initial public offering:learn geo-graphy,and learn it in motion.To the degree that Facebook can turn metaphorical data-mining rou-tines into material harvests of quarterly revenue streams by placing ads before consumers’eyes in the quantitatively optimized time,place,and social context of the user’s instantaneous experience,Wall Street’s automated high-speed trading algorithms will have a new,unprecedented means of extracting surplus value through manipulations of space–time. Widespread social networking,mobile advertising, and evolutionary Wall Street infrastructures of auto-mated financialization coalesce in Hagerstrandian time–geography futures collateralized by the com-modification of the human attention span.The num-ber of Facebook users who access the service’s mobile version at least once a month is now819mil-lion,and mobile ads grew from near zero in the sec-ond quarter of2012to41%of total ad revenue in the second quarter of2013.‘Facebook’s results elated investors’,the New York Times reports,quoting one securities analyst who distills the singular essence of all the details in the earnings report:‘This company is becoming more and more of a mobile company’(Goel,2013).

Facebook,of course,is only one of the expanding array of mobilized,spatially referenced data streams enabling the neogeography and visualization oppor-tunities surveyed by Johnston et al.,and these new social media ecosystems are only the most recent additions to the social observation infrastructures of postindustrial information societies(Curry,1997; Goss,1995).Johnston et al.(p.10)are correct to emphasize that‘a secure background in quantitative analyses is necessary for an informed citizenry in a society heavily driven by numbers’and‘data do not“just exist”’but are created and performed through evolving social and institutional prac-tice.Mobilization has profound implications for Johnston et al.’s curriculum proposals,as public institutions and social scientists scramble to follow private corporations and the military into the new frontiers of big data.As more public and private institutions become informational enterprises,the tough theoretical questions of previous generations (Abler et al.,1971;Curry,1996;Harvey,1969; Turing,1950)become banal shocks of everyday performativity,exacerbating dilemmas of law and ethics.Which paths of individuals’constantly evolving data trails will be observed,linked with other micro-or summary-level data,or replicated as part of new recombinant data ecosystems?What inferences will be drawn from selective,partial, and situated views of the intricate and often contra-dictory data shadows of individuals and social col-lectives?Will it become standard procedure for prosecutors to regard the failure to carry a cell phone as evidence of conspiracy(Schmidt and Hipp,2007),especially among those who write on inflammatory topics such as‘inequality’and ‘gentrification’(Bernt and Holm,2005)?

As corporations,government agencies,and grassroots social movements all face competitive pressures to participate in the emerging standpoint epistemologies of big data,how do we cope with the ubiquitous explosions of Heisenberg uncer-tainty in the digital,mobilized‘cognisphere’(Hayles,2006)?Consider the breathtaking analyti-cal possibilities demonstrated by Shelton et al. (2012)and Crampton et al.’s(2012)extraordinary spatiotemporal analyses of Twitter feeds,in rela-tion to Castells’(2012:219)portrayal of social media social movements as transforming‘[e]nthu-siastic networked individuals’into‘a conscious collective actor’of‘connections between networks of neural networks from human brains stimulated by signals from a communication environment through communication networks’.One way to reconcile the speedy pseudopositivism of tweet-space analysis with social–theoretical accounts of social media social movements is to understand these approaches as separate vantage points for the human understanding of exogenously given,real phenomena unfolding through space and time.Yet

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these‘realities’change at velocities mediated by code that quickly and constantly aggregates mil-lions of separate decisions,communications, actions,and(re)actions.Such processing speeds cannot be matched by the slow pace of individual human cognition and understanding,and indeed the advocates of big data are insistent on a radical spirit of inductive empiricism.Let the data mining routines find correlations unburdened by theory, we are told:

Society will need to shed some of its obsession for caus-ality in exchange for simple correlations:not knowing why,but only what.This overturns centuries of estab-lished practices and challenges our most basic under-standing of how to make decisions and comprehend reality.(Mayer-Scho¨nberger and Cukier,2013:7)

Moreover,people around the world—from the multitudes of China’s‘human-flesh search engine’(Wang et al.,2010)to the‘heads-down tribes’(Nam,2013:D2)of millions everywhere‘con-stantly checking e-mail or social media’—are com-ing to understand that cognisphere realities are up for grabs.Social media strategies are typically the first step for any contemporary social movement. There are fast-growing industries for online reputa-tion management(creating demand for new kinds of vetting by online private investigation services), identity theft(identity protection services),search engine optimization,click fraud,and all sorts of other informational performances that defy the old caricatures of naive positivist objective observation of a passive external reality.Those old caricatures have deceived us on the history of positivism,how-ever(Scharff,1995),and the irony is that today’s poststructural‘datasphere’is bringing us back to prepositivist Cartesian metaphysical doctrines applied to exabytes of data.Not only does big data erode the dichotomy between production and con-sumption,billions of consumers(willing or not)pro-duce the valuable data assets of a handful of large technology companies—as the enterprise reworks the relations between action and observation and subject/object duality.

When mass popular collectives face centralized, place-bound hierarchies of coercion,the fast performative realities of mobilized social data offer extraordinary transformative potential through‘net-works of outrage and hope’(Castells,2012).Neo-geography,big data,and social media deliver pragmatism in real time:through communication,‘Events turn into objects,things with meaning.They may be referred to when they do not exist,and thus be operative among things distant in space and time, through vicarious presence in a new medium’(Dewey,[1925]1938:386).Yet there is a simulta-neous threat of dehumanization:The stunning effi-ciencies of automation and code require far fewer human geographers than yesteryear’s quantitative revolution,while the infrastructure of algorithms, laws,and servers enables greater autonomy for digi-tal individuals(Curry,1997):

Brute efficiencies and inarticulate consummations as soon as they can be spoken of are liberated from local and accidental contexts,and are eager for naturaliza-tion in any non-insulated communicating part of the world.Events when once they are named lead an inde-pendent and double life.In addition to their original existence,they are subject to ideal experimentation: their meanings may be infinitely combined and re-arranged in imagination,and the outcome of this inner experimentation—which is thought—may issue forth in interaction with crude or raw events...

Where communication exists,things in acquiring meaning thereby acquire representatives,surrogates, signs and implicates,which are infinitely more amen-able to management,more permanent and accommo-dating than events in their first estate.(Dewey, [1925]1938:386)

Student big data:The new T test

The third dimension of the new quantitative revolu-tion involves the role of data on the teaching and learning process itself in our current Gutenberg moment(Schuurman,2013)of shifting digital cul-tures of geographical knowledge production.To understand the implications of the new curriculum that is becoming part of students’lives,consider a vision of Harvard offered by Gary King,a quantita-tive political scientist whose work on ecological inference has engaged with geographical themes (Anselin,2000;King,1997,2000).In a presentation

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to Harvard’s Board of Overseers in February2012, King argued that the greatest threat to Harvard is investment in research and development on the teaching process undertaken by for-profit,online universities.

Meanwhile,seventy percent of Americans don’t get a college degree.You might say,“Oh,that’s really bad.”

Or you might say,“Oh,that’s a different clientele.”

But what it really is is a revenue source.It’s an enor-mous revenue source for these private corporations.

(quoted in Heller,2013:85)

In response,King advocates that online education be transformed from a dissemination function into something that treats the student experience as‘a precious data-gathering resource’.‘We could do this at Harvard’,King explained,in a way that could measure educational activities in unprecedented detail,and in context,‘...we could instrument every student,every classroom,every administra-tive office,every house,every recreational activity, every security officer,everything.We could basi-cally get the information about everything that goes on here,and we could use it for the students’(quoted in Heller,2013:85).King’s presentation to the administrators sketched a clear image of what edu-cation might look like:

A giant,detailed data pool of all activity on the campus

of a school like Harvard,he said,might help students resolve a lot of the ambiguities in college life.“Right now,if a student wants to learn,What should I do if I want to become an M.D.?—well,What do they do?”

he asked.“They talk to their advisor.They talk to some previous students.They get some advice.But,instead of talking to some previous students,how about they talk to ten thousand previous students?”With enough data over

a long enough period,you could crunch inputs and prob-

abilities and tell students,with a high degree of accu-racy,exactly which choices and turns to make to get where they wanted to go in life.He went on,“Every time you go to https://www.wendangku.net/doc/8915918987.html,,you are the subject of a rando-mized experiment.Every time you search on Google, you are the subject of an experiment.Why not every time a student here does something?”(Heller,2013:85) King’s vision is the latest proposal in Harvard’s response to the current rage for massive open online courses(MOOCs),and a wave of digital educational initiatives:Coursera,Udacity,the joint Harvard-MIT spinoff EdX,and of course the behemoth Uni-versity of Phoenix—the US’s largest university as measured by enrollment,with almost half a million students(Wilson,2011).King has developed an ini-tial pilot test of digital‘flipped class’approaches to illustrate some of the pedagogical possibilities (King and Sen,2013a,2013b),but the long-term vision is what matters here.A giant,detailed pool of all activity,derived from‘instrumenting’every student,every classroom...everything.Just for a moment,set aside the conditions of possibility of instrumenting or measuring‘everything’,and for-give King for the model mis-specification defining ‘where you want to go in life’as an exogenous vari-able;for a moment,just consider the implications a few years from now when Harvard might have about the same number of data points on each student (about1500)that the marketing firm Axciom cur-rently has on hundreds of millions of consumers (Singer,2012).What would it mean to resolve‘a lot of the ambiguities in life’with‘inputs and probabil-ities’to‘tell students,with a high degree of accu-racy,exactly which choices and turns to make’? Suppose the data confirm the hypotheses of the cur-rent enthusiasm for magnetic resonance imaging–detectable‘neuroleadership’(Hill,2013;Waldman et al.,2011)and tell us that it’s the aggressive, selfish students who have the highest probability of‘getting where they want to go in life’?The data might tell us that the current black market off-label use of Ritalin and other‘cognitive enhancements’on competitive university campuses(Lamkin, 2012)receives multivariate,randomized-trial vali-dation confirming the efficacy of academic ster-oids.If the past decade’s Ivy Leage-to-Wall Street pipeline is any guide,the‘inputs and prob-abilities’will justify a comprehensive curriculum in exploitative financial alchemy(subprime mort-gages and credit default swaps),and economics and philosophy courses stripped of any ethics or irony so that graduates are fully prepared to advocate trillion-dollar financial-sector bailouts financed through harsh austerity measures on the poor and working classes.King’s manifesto for a giant, detailed pool of all activity is reminiscent of

32Dialogues in Human Geography4(1)

Gould’s(1981)‘Letting the Data Speak for Themselves’—torn away from the etymological and ontological challenges of understanding the meaning of Peter’s provocation:

The title is,of course,absurd:inanimate data can never speak for themselves,and we always bring to bear some conceptual framework,either intuitive and ill-formed,or tightly and formally structured,to the task of investigation,analysis,and interpretation.

So let me confess that I chose it to be deliberately provocative;and yet,like the Theatre of the Absurd, there might be a deep vein of truth underneath such

a provocation.The title could be profound.(Gould,

1981:166)

It is profound.Big data cognitive–cultural capit-alism is fast reconfiguring geographies of education, rescaling the time–space experience of teaching, learning,and the tethers connecting geographical practice with the written word(Curry,1996).The algorithmic predestination offered by King and oth-ers is code that risks destruction of the happenstance of learning,the unexpected discovery of new desti-nations.Penn State’s Anthony Robinson,who is now preparing for an MOOC of‘the world’s largest cartography class’,discovered the field by accident like so many other geographers:

I started my undergraduate education as an electrical

engineering major.Then I just randomly took a human geography class,and it completely woke me up.Right away I knew I wanted to be a geographer.(quoted in Miller,2013)

There is an exciting,hallucinogenic sense of enlightenment possibility here,a joyous vertigo in the realization that what Robinson calls his‘gate-way drug to mapping’will offer cartographic reve-lation to(a current estimate of)29,400students.Yet what can it mean to‘take a course’with29,399other students?And what will it mean in a world where King’s data-driven probability estimates will entrench early choices along trajectories that will minimize the disturbance terms of students who ‘just randomly’take human geography classes? To be sure,there are many new possibilities enabled by the digital production of scale:You can imagine Gould doing lots of his familiar locational preference surveys to create dynamic mental maps of the collective geographical imagination of a class this size.These new possibilities will last for exactly one generation,until the consolidation of celebrity singularity.This is the point at which the vast trove of detailed MOOC data yield unprecedented preci-sion in the measurement of pedagogy,student engagement,learning outcomes,and elasticity of market demand:It will be algorithmically possible and administratively irresistible to identify the‘best cartography professor’(or to create a digital mash-up of separate instructors into the quantitatively optimized cartography course)and then to dispense with all the other mediocre wannabes.Such rank-and-yank practices are already standard procedures in many competitive enterprises,and the new fron-tier of struggle now involves questions of how to define‘best’in ways that can be partially automated through existing systems of data surveillance,in order to yield a single,unambiguous dimension of rank order to maximize prestige for the numerator of1/n subject to measures designed to push n!1 as far as possible for any particular job opening or other institutional purpose.As Turing(1950:449) would have it,‘these are possibilities of the near future,rather than Utopian dreams’,and many of them are being refined at places like Singularity University located inside the NASA Research Park in Silicon Valley(Lanier,2010,2013).The self-replicating infrastructure of competition and market metrics is suppressing the material‘multidimen-sionality’(Gould,1979:145)of being a human geographer even as the multidimensional analytical frontiers of human-experienced geographies—many of them now mapped by data-mining routines and autopilot bots—continue to expand.

As the new quantitative revolution of postem-ployment educational automation removes the lower rungs of the job ladders for aspiring scholars of what Jamie Peck calls the MOOCetariat,studen-tized big data,and non-Euclidian,post-Cartesian teacher/student geographies create new market opportunities in suspicion and surveillance.At MOOC scale,the only reliable way to ensure that ‘taking a course’is not subjected to the same radical disruption of meaning that Facebook has inflicted on‘friend’is to sacrifice the inescapably subjective,

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flawed human social relations of trust.Human trust is under siege replaced by an expanding universe of surveillance.For-credit MOOCs now involve algo-rithms to proctor examinations under the surveil-lance of live images,signatures,and the typing rhythms of students’keystrokes(Eisenberg,2013). EdX,the online Harvard-MIT consortium,is imple-menting artificial intelligence systems to grade essays(Markoff,2013).The‘senior director of tech-nology evangelism’for the online learning manage-ment system Blackboard is working on digital detection systems to measure how‘authors write in ways that amount to a kind of fingerprint’(Young,2012).The most widely used educational software on the planet(the plagiarism detection ser-vice https://www.wendangku.net/doc/8915918987.html,)evaluates students’writing against an ever-expanding database of billions of documents,using algorithms originally designed ‘to detect regularities in large databases of brain-waves’(Barrie,2008:18)https://www.wendangku.net/doc/8915918987.html,’s parent company iParadigms,LLC,also markets a similar service for institutions needing to verify the origin-ality of work by graduate students,postdoctoral researchers,college and university faculty,or any other human content creator meriting digitized guilty-until-proven-innocent treatment.Several court decisions rejecting students’challenges to iParadigms’practices have established clear prece-dents for the emerging laws of this new quantitative revolution.If geography’s heritage of scientific explanation(Harvey,1969)is retrospectively understood as a search for the laws of spatial orga-nization(Abler et al.,1971)in the spirit of Newto-nian social physics,the new era of automated postpositivism is governed by a decisively general-ized relativity of space–time.The new geographies of MOOCs and ubiquitous social media are rescal-ing Hagerstrand’s time–geographic constraints and Tobler’s infamous first law of geography—‘all things are related,but near things are more related than distant things’—into a new world of constantly evolving scales of adaptive cybernetic performance. The global scale of Internet connectivity is juxta-posed with the microsurveillance of student key-strokes and individual word choices,while the laws of online space–time are increasingly governed by end-user license agreements,copyrights,patents,trademarks,and all the other legal force fields of digitized intellectual property.

The new revolution:The neoliberal noo¨sphere

Johnston et al.(2014:17)present a compelling case that the opportunity to learn quantitative spatial sci-ence‘should not be denied students’.This is a call that merits our strongest support;we have fallen far since the days when a book like Spatial Organiza-tion(Abler et al.,1971)could be used as a text for a second-year geography course.My purpose in this commentary,however,has been to take for granted the value,rigor,and creative power of Johnston et al.’s curriculum—and then to look farther afield, to consider the external threats to Johnston et al.’s vision of critical spatial https://www.wendangku.net/doc/8915918987.html,pared with spatial science‘as pioneered50years ago’,(p.17) today’s quantitative revolution takes place in a con-text that is at once strikingly new,and yet all too familiar.Just as progressive quantitative geogra-phers in the1960s struggled to find emancipatory possibilities in the war-machine quantification tools deployed by the‘IBM machine with legs’(the phrase used by Barry Goldwater to praise U.S. Defense Secretary Robert McNamara,UPI(United Press International),1962:22),today’s progressive geographers must work in the shadow of spatial science as co-opted by Obama’s kill-list drones,the exponentiated networks of the NSA’s‘hop analysis’surveillance and the pervasive new data ecologies of private marketing firms in an increasingly unstable era of cognitive–cultural capital accumulation.Yet if the progressive spirit is the same,other things have changed a great deal;this is where we need to reconsider the memories of our previous quantitative revolution.Susan Hanson(1993:555)recalls arguing with one of her mentors at Northwestern,as she questioned the notion of economic man and other restrictive assumptions underlying the models that were the centerpiece of our education...Unable to dampen my hot-headed attacks,this teacher finally exploded in exasperation and probably desperation:“Never question the assumptions!”,words that have ever since been branded on my brain.

34Dialogues in Human Geography4(1)

From another perspective,Trevor Barnes(2013, p.4)reminds us of the humanist critics of the quantifiers in the1970s,who‘argued geographical context is frequently left out in quantitative studies because it cannot be expressed in numerical form...what is often lost is context,which cannot be put into an equation’.

Both of these factors are changing in the new quantitative revolution.Big data enables and encourages empiricist data-mining logics unhinged from the positivist framework of assumptions, hypotheses,and causal explanation:When Google researchers designed a system to find distinctive patterns in billions of search queries that correlated with influenza outbreaks,they did not begin with any hypotheses on which search terms would be most likely or relevant:‘they didn’t know,and they designed a system that didn’t care’(Mayer-Scho¨n-berger and Cukier,2013:2).Question every assumption,and let the data speak for themselves. And as individuals and institutions spend ever more time online(by choice,peer pressure,or various degrees of commercial or legal coercion)context is steadily being redefined and subject to partially automated infrastructures of data production and linkage.Each year,more of what human geogra-phers would consider‘context’is,in fact,being expressed in numerical form.

Taken together,the three shifts outlined in this commentary—the torrential acceleration of data flows,the circulation and partially autonomous replication of mobile data streams,and the quanti-fied surveillant austerity of neoliberal performance assessment and online education—seem to be reconstituting some of the most important debates of geography from the20th century.Big data and cloud computing are presented,quite proudly,as let-ting the data speak for themselves(Gould,1981). Digital reality is ransacked not in search of theory (Smith,1979)but in pursuit of eyeballs,page views, and click-throughs constituted as rents extracted from the global attention span.Such a phenomenon has only recently come into pragmatist existence with the new abilities to observe and quantify online human attention in real time.Analyses of‘[e]nthu-siastic networked individuals’becoming‘a con-scious collective actor’(Castells,2012:219)allow those at the intersections of vast flows of social media data to assign an‘autonomous ontological status’to networked social aggregates,returning us to the Sauerian heritage of the‘superorganic’(Duncan,1980:198).If the advocates of big data and crowdsourcing are to be believed,the‘evolving global brain’can be monitored from sites like MIT’s Center for Collective Intelligence(Revkin,2012), thus achieving a belated quantification of Pierre Teilhard de Chardin’s(1956:109,103)idea of the noo¨sphe`re—from the Greek noos,‘mind,’tsphaera,‘sphere’—denoting a planetary system of ‘reflexive awareness’and a‘superstage of con-sciousness’in‘a special layer of thinking and cul-tured substance all around the globe’.

Adapting to this new quantitative revolution requires a new synthesis of analytical and political sophistication.In the automated noo¨sphere of self-replicating data,quantitative human geography will be perpetually at risk of becoming just another de-skilled,dehumanized enterprise:McNamara,the IBM machine with legs,is now in the Cloud,in the cognisphere above the Smarter Cities of the Smarter Planet.Johnston et al.’s(2014)proposal gives us a powerful case that we need to inspire and educate a new generation of spatial scientists;yet it is imperative that we decide if we wish to protect a truly human geography—geography as understood, lived,performed,and learned by humans.It is no coincidence that critical human geographers are deeply engaged with posthumanist philosophies at precisely the historical moment when neuromark-eters and Silicon Valley visionaries at Singularity University are also smitten with the idea that‘con-sciousness,mind,and memory...are nothing more and nothing less than complex movements of mat-ter’(Hinchliffe,2009:564).Algorithms are coloniz-ing the inherently human legacy of geographers’debates during the heady blend of political struggle and methodological innovation that defined the quantitative revolution of the1960s.Today,we’re forced into a race,as we teach a generation of spatial scientists in an age when more and more of their pro-fessional skills are coded into networked expert sys-tems.This is the true quantitative revolution,when the noo¨sphe`re of big data,with its ruthlessly perfor-mative effectiveness of measures of popularity,

Wyly35

audience,and‘impact’,evolves into something that,for better or worse,is treated as a‘conscious collective actor’(Castells,2012:219)through the statistically unique assemblage of algorithmically optimized‘networks of neural networks’from ‘human brains stimulated by signals from a com-munication environment through communication networks’.Google’s mantra,‘Nobody’s as smart as everybody’,symbolizes the accelerating replace-ment of human professional expertise by the big data‘osmotic self that is able to absorb new infor-mation about people and situations even before encountering them directly’(Lanier,2013:285). Human craft labor that could once have earned a master’s or a doctorate can now be distilled into the latest app that evolves in a partially autonomous digital ecosystem of constant flows of social data. We have a new quantitative revolution,and this time the most dangerous revolutionaries are not people brandishing mathematical models while dreaming up provocative titles about the Augean stables (Gould,1977)or declaring‘Never question the assumptions!’(Hanson,1993:555)and‘By our theories you shall know us’(Harvey,1969:486). Now,the models arrive brandishing people—collections of thousands and millions of socially networked digital individuals in an expanding neoliberal noo¨sphe`re.

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对翻译中异化法与归化法的正确认识

对翻译中异化法与归化法的正确认识 班级:外语学院、075班 学号:074050143 姓名:张学美 摘要:运用异化与归化翻译方法,不仅是为了让读者了解作品的内容,也能让读者通过阅读译作,了解另一种全新的文化,因为进行文化交流才是翻译的根本任务。从文化的角度考虑,采用异化法与归化法,不仅能使译文更加完美,更能使不懂外语的人们通过阅读译文,了解另一种文化,促进各民族人们之间的交流与理解。翻译不仅是语言符号的转换,更是跨文化的交流。有时,从语言的角度所作出的译文可能远不及从文化的角度所作出的译文完美。本文从翻译策略的角度,分别从不同时期来说明人们对异化法与归化法的认识和运用。 关键词:文学翻译;翻译策略;异化;归化;辩证统一 一直以来,无论是在我国还是在西方,直译(literal translation)与意译(liberal translation)是两种在实践中运用最多,也是被讨论研究最多的方法。1995年,美籍意大利学者劳伦斯-韦努蒂(Lawrence Venuti)提出了归化(domestication)与异化(foreignization)之说,将有关直译与意译的争辩转向了对于归化与异化的思考。归化与异化之争是直译与意译之争的延伸,是两对不能等同的概念。直译和意译主要集中于语言层面,而异化和归化则突破语言的范畴,将视野扩展到语言、文化、思维、美学等更多更广阔的领域。 一、归化翻译法 Lawrwnce Venuti对归化的定义是,遵守译入语语言文化和当前的主流价值观,对原文采用保守的同化手段,使其迎合本土的典律,出版潮流和政治潮流。采用归化方法就是尽可能不去打扰读者,而让作者向读者靠拢(the translator leaves the reader in peace, as much as possible, and moves the author towards him)。归化翻译法的目的在于向读者传递原作的基本精神和语义内容,不在于语言形式或个别细节的一一再现。它的优点在于其流利通顺的语言易为读者所接受,译文不会对读者造成理解上的障碍,其缺点则是译作往往仅停留在内容、情节或主要精神意旨方面,而无法进入沉淀在语言内核的文化本质深处。 有时归化翻译法的采用也是出于一种不得已,翻译活动不是在真空中进行的,它受源语文化和译语文化两种不同文化语境的制约,还要考虑到两种文化之间的

翻译中的归化与异化

“异化”与“归化”之间的关系并评述 1、什么是归化与异化 归化”与“异化”是翻译中常面临的两种选择。钱锺书相应地称这两种情形叫“汉化”与“欧化”。A.归化 所谓“归化”(domestication 或target-language-orientedness),是指在翻译过程中尽可能用本民族的方式去表现外来的作品;归化翻译法旨在尽量减少译文中的异国情调,为目的语读者提供一种自然流畅的译文。Venuti 认为,归化法源于这一著名翻译论说,“尽量不干扰读者,请作者向读者靠近” 归化翻译法通常包含以下几个步骤:(1)谨慎地选择适合于归化翻译的文本;(2)有意识地采取一种自然流畅的目的语文体;(3)把译文调整成目的语篇体裁;(4)插入解释性资料;(5)删去原文中的实观材料;(6)调协译文和原文中的观念与特征。 B.“异化”(foreignization或source-language-orientedness)则相反,认为既然是翻译,就得译出外国的味儿。异化是根据既定的语法规则按字面意思将和源语文化紧密相连的短语或句子译成目标语。例如,将“九牛二虎之力”译为“the strength of nine bulls and two tigers”。异化能够很好地保留和传递原文的文化内涵,使译文具有异国情调,有利于各国文化的交流。但对于不熟悉源语及其文化的读者来说,存在一定的理解困难。随着各国文化交流愈来愈紧密,原先对于目标语读者很陌生的词句也会变得越来越普遍,即异化的程度会逐步降低。 Rome was not built in a day. 归化:冰冻三尺,非一日之寒. 异化:罗马不是一天建成的. 冰冻三尺,非一日之寒 异化:Rome was not built in a day. 归化:the thick ice is not formed in a day. 2、归化异化与直译意译 归化和异化,一个要求“接近读者”,一个要求“接近作者”,具有较强的界定性;相比之下,直译和意译则比较偏重“形式”上的自由与不自由。有的文中把归化等同于意译,异化等同于直译,这样做其实不够科学。归化和异化其实是在忠实地传达原作“说了什么”的基础之上,对是否尽可能展示原作是“怎么说”,是否最大限度地再现原作在语言文化上的特有风味上采取的不同态度。两对术语相比,归化和异化更多地是有关文化的问题,即是否要保持原作洋味的问题。 3、不同层面上的归化与异化 1、句式 翻译中“归化”表现在把原文的句式(syntactical structure)按照中文的习惯句式译出。

翻译的归化与异化

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万方数据

万方数据

翻译的归化与异化 作者:熊启煦 作者单位:西南民族大学,四川,成都,610041 刊名: 西南民族大学学报(人文社科版) 英文刊名:JOURNAL OF SOUTHWEST UNIVERSITY FOR NATIONALITIES(HUMANITIES AND SOCIAL SCIENCE) 年,卷(期):2005,26(8) 被引用次数:14次 参考文献(3条) 1.鲁迅且介亭杂文二集·题未定草 2.刘英凯归化--翻译的歧路 3.钱钟书林纾的翻译 引证文献(15条) 1.郭锋一小议英语翻译当中的信达雅[期刊论文]-青春岁月 2011(4) 2.许丽红论汉英语言中的文化差异与翻译策略[期刊论文]-考试周刊 2010(7) 3.王笑东浅谈汉英语言中的差异与翻译方法[期刊论文]-中国校外教育(理论) 2010(6) 4.王宁中西语言中的文化差异与翻译[期刊论文]-中国科技纵横 2010(12) 5.鲍勤.陈利平英语隐喻类型及翻译策略[期刊论文]-云南农业大学学报(社会科学版) 2010(2) 6.罗琴.宋海林浅谈汉英语言中的文化差异及翻译策略[期刊论文]-内江师范学院学报 2010(z2) 7.白蓝跨文化视野下文学作品的英译策略[期刊论文]-湖南社会科学 2009(5) 8.王梦颖探析汉英语言中的文化差异与翻译策略[期刊论文]-中国校外教育(理论) 2009(8) 9.常晖英汉成语跨文化翻译策略[期刊论文]-河北理工大学学报(社会科学版) 2009(1) 10.常晖对翻译文化建构的几点思考[期刊论文]-牡丹江师范学院学报(哲学社会科学版) 2009(4) 11.常晖认知——功能视角下隐喻的汉译策略[期刊论文]-外语与外语教学 2008(11) 12.赵勇刚汉英语言中的文化差异与翻译策略[期刊论文]-时代文学 2008(6) 13.常晖.胡渝镛从文化角度看文学作品的翻译[期刊论文]-重庆工学院学报(社会科学版) 2008(7) 14.曾凤英从文化认知的视角谈英语隐喻的翻译[期刊论文]-各界 2007(6) 15.罗琴.宋海林浅谈汉英语言中的文化差异及翻译策略[期刊论文]-内江师范学院学报 2010(z2) 本文链接:https://www.wendangku.net/doc/8915918987.html,/Periodical_xnmzxyxb-zxshkxb200508090.aspx

归化与异化翻译实例

翻译作业10 Nov 15 一、请按归化法(Domestication)翻译下列习语。 Kill two birds with one stone a wolf in sheep’s clothing strike while the iron is hot. go through fire and water add fuel to the flames / pour oil on the flames spring up like mushrooms every dog has his day keep one’s head above water live a dog’s life as poor as a church mouse a lucky dog an ass in a lion’s skin a wolf in sheep’s clothing Love me, love my dog. a lion in the way lick one’s boots as timid as a hare at a stone’s throw as stupid as a goose wet like a drown rat as dumb as an oyster lead a dog’s life talk horse One boy is a boy, two boys half a boy, and three boys nobody. Man proposes, God disposes. Cry up wine and sell vinegar (cry up, to praise; extol: to cry up one's profession) Once bitten, twice shy. An hour in the morning is worth two in the evening. New booms sweep clean. take French leave seek a hare in a hen’s nest have an old head on young shoulder Justice has long arms You can’t teach an old dog Rome was not built in a day. He that lives with cripples learns to limp. Everybody’s business is nobody’s business. The more you get, the more you want. 二、请按异化法(foreignization)翻译下列习语。 Kill two birds with one stone a wolf in sheep’s clothing

翻译术语归化和异化

归化和异化这对翻译术语是由美国著名翻译理论学家劳伦斯韦努蒂(Lawrence Venuti)于1995年在《译者的隐身》中提出来的。 归化:是要把源语本土化,以目标语或译文读者为归宿,采取目标语读者所习惯的表达方式来传达原文的内容。归化翻译要求译者向目的语的读者靠拢,译者必须像本国作者那样说话,原作者要想和读者直接对话,译作必须变成地道的本国语言。归化翻译有助于读者更好地理解译文,增强译文的可读性和欣赏性。 异化:是“译者尽可能不去打扰作者,让读者向作者靠拢”。在翻译上就是迁就外来文化的语言特点,吸纳外语表达方式,要求译者向作者靠拢,采取相应于作者所使用的源语表达方式,来传达原文的内容,即以目的语文化为归宿。使用异化策略的目的在于考虑民族文化的差异性、保存和反映异域民族特征和语言风格特色,为译文读者保留异国情调。 作为两种翻译策略,归化和异化是对立统一,相辅相成的,绝对的归化和绝对的异化都是不存在的。在广告翻译实践中译者应根据具体的广告语言特点、广告的目的、源语和目的语语言特点、民族文化等恰当运用两种策略,已达到具体的、动态的统一。 归化、异化、意译、直译 从历史上看,异化和归化可以视为直译和意译的概念延伸,但又不完全等同于直译和意译。直译和意译所关注的核心问题是如何在语言层面处理形式和意义,而异化和归化则突破了语言因素的局限,将视野扩展到语言、文化和美学等因素。按韦努蒂(Venuti)的说法,归化法是“把原作者带入译入语文化”,而异化法则是“接受外语文本的语言及文化差异,把读者带入外国情景”。(Venuti,1995:20)由此可见,直译和意译主要是局限于语言层面的价值取向,异化和归化则是立足于文化大语境下的价值取向,两者之间的差异是显而易见的,不能混为一谈。 归化和异化并用互补、辩证统一 有些学者认为归化和异化,无论采取哪一种都必须坚持到底,不能将二者混淆使用。然而我们在实际的翻译中,是无法做到这么纯粹的。翻译要求我们忠实地再现原文作者的思想和风格,而这些都是带有浓厚的异国情调的,因此采用异化法是必然;同时译文又要考虑到读者的理解及原文的流畅,因此采用归化法也是必然。选取一个策略而完全排除另一种策略的做法是不可取的,也是不现实的。它们各有优势,也各有缺陷,因此顾此失彼不能达到最终翻译的目的。 我们在翻译中,始终面临着异化与归化的选择,通过选择使译文在接近读者和接近作者之间找一个“融会点”。这个“融会点”不是一成不变的“居中点”,它有时距离作者近些,有时距离读者近些,但无论接近哪

翻译中的归化与异化

姓名:徐中钧上课时间:T2 成绩: 翻译中的归化与异化 归化与异化策略是我们在翻译中所采取的两种取向。归化是指遵从译出语文化的翻译策略取向,其目的是使译文的内容和形式在读者对现实了解的知识范围之内,有助于读者更好地理解译文,增强译文的可读性。异化是指遵从译入语文化的翻译策略取向,其目的是使译文保存和反映原文的文化背景、语言传统,使读者能更好地了解该民族语言和文化的特点。直译和意译主要是针对的是形式问题,而归化和异化主要针对意义和形式得失旋涡中的文化身份、文学性乃至话语权利的得失问题,二者不能混为一谈。 在全球经济一体化趋势日益明显的今天,人们足不出门就能与世界其他民族的人进行交流。无论是国家领导人会晤、国际经济会议,还是个人聚会、一对一谈话,处于不同文化的两个民族都免不了要进行交流。如果交流的时候不遵从对方的文化背景,会产生不必要的误会,造成不必要的麻烦。在2005年1月20 日华盛顿的就职典礼游行活动中,布什及其家人做了一个同时伸出食指和小指的手势。在挪威,这个手势常常为死亡金属乐队和乐迷使用,意味着向恶魔行礼。在电视转播上看到了这一画面的挪威人不禁目瞪口呆,这就是文化带来的差异。人们日常生活中的习语、修辞的由于文化差异带来的差别更是比比皆是,如以前的“白象”电池的翻译,所以文化传播具有十分重要的意义。由此可见,借助翻译来传播文化对民族间文化的交流是很有必要的。 一般来说,采取归化策略使文章变得简单易懂,异化使文章变得烦琐难懂。归化虽然丢掉了很多原文的文化,但使读者读起来更流畅,有利于文化传播的广度。采取异化策略虽然保存了更多的异族文化,能传播更多的异族文化,有利于文化传播的深度,但其可读性大大降低。归化和异化都有助于文化的传播,翻译时应注意合理地应用归化与异化的手段。对于主要是表意的译文,应更多地使用归化手段,反之则更多地使用异化手段。 要使翻译中文化传播的效果达到最好,译者应该考虑主要读者的具体情况、翻译的目的、译入文的内容形式等具体情况而动态地采取归化与异化的手段。 文章字符数:920 参考文献: 论异化与归化的动态统一作者:张沉香(即讲义) 跨文化视野中的异化/归化翻译作者:罗选民https://www.wendangku.net/doc/8915918987.html,/llsj/s26.htm

翻译的归化与异化

【摘要】《法国中尉的女人》自1969年面世以来,凭借着高度的艺术价值,吸引了国内外学者的眼球。在中国市场上也流传着此书的多个译本,本文就旨在透过《法国中尉的女人》中的两处题词的译作分析在具体翻译文本中如何对待归化与异化的问题。 【关键词】《法国中尉的女人》;题词;归化;异化 一、归化与异化 在翻译领域最早提出归化与异化两个词的学者是美国翻译学者韦努蒂。归化一词在《翻译研究词典》中的定义为:归化指译者采用透明、流畅的风格以尽可能减弱译语读者对外语语篇的生疏感的翻译策略。异化一词的定义为:指刻意打破目的语的行文规范而保留原文的某些异域特色的翻译策略。韦努蒂主张在翻译的过程中更多的使用异化,倡导看起来不通顺的译文,注重突出原文的异域风格、语言特色与文化背景。 二、如何看待归化与异化 鲁迅说对于归化与异化,我们不能绝对的宣称哪种是绝对的好的,另一种是绝对的不好的。翻译的过程中归化与异化是相辅相成互相补充的,具体使用哪种方法不仅需要依据翻译目的以及译文的读者群来判断。这也正是本文对待归化异化的一个态度。下面就通过分析刘蔺译本与陈译本在处理《法国中尉的女人》第五章的引言丁尼生《悼念集》时的例子来具体分析这一点。对于原文 at first as death, love had not been, or in his coarsest satyr-shape had bruised the herb and crush’d the grape, 刘蔺译本将此处翻译为 啊,天哪,提这样的问题 又有保益?如果死亡 首先意味着生命了结, 那爱情,如果不是 在涓涓细流中戛然中止, 就是一种平庸的友情, 或是最粗野的色迷 在树林中肆意饕餮, 全不顾折断茎叶, 揉碎葡萄―― 而此时陈译本却将此诗译作 哦,我啊,提出一个无益的问题 又有何用?如果人们认为死亡 就是生命的终结,那么,爱却不是这样, 否则,爱只是在短暂的空闲时 那懒散而没激情的友谊, 或者披着他萨梯粗犷的外套 已踩伤了芳草,并摧残了葡萄, 在树林里悠闲自在,开怀喝吃。 两篇译作各有千秋,从这首诗整体着眼刘蔺译本更趋向于归化手法,陈译本更倾向于异化处理。刘蔺译本将satyr一词译色迷采用了归化的技巧,而陈译本却将satyr一词译为萨梯,采用了异化的手法。satyr原指人羊合体的丛林之神,其实刘蔺译本与陈译本在处理satyr 时采用不同的方法就是因为翻译目的及读者文化群不同引起的。1986年出的刘蔺译本出版时,

中国旅游文本汉英翻译的归化和异化演示教学

中国旅游文本汉英翻译的归化和异化

中国旅游文本汉英翻译的归化和异化 内容摘要:自改革开放政策执行以来,我国旅游业一直呈现迅速繁荣发展趋势,旅游业在我国国民经济发展中扮演着十分重要的角色。与此同时,旅游类翻译已经被视为一条将我国旅游业引往国际市场的必经之路。为了能够让国外游客更清楚地了解中国的旅游胜地,我们应该对旅游翻译加以重视。尽管国内的旅游资料翻译如同雨后春笋般涌现,但在旅游翻译中仍存在许多问题,尤其是翻译策略的选择问题。归化与异化作为处理语言形式和文化因素的两种不同的翻译策略,无疑对旅游翻译的发展做出了巨大贡献。本文将重点讨论在汉英旅游翻译中,译者该如何正确的处理归化和异化问题,实现归化和异化的有机结合,从而达到理想的翻译水平。从归化与异化的定义、关系、以及归化和异化在旅游翻译中的应用与意义进行论述。 关键词:旅游文本归化翻译异化翻译 关于翻译中归化和异化的定义,国内外的专家学者已经做了很多的描述。为了使得本文读者更好地了解什么是翻译中的归化和异化,作者将介绍这两种翻译方法的关键不同,包括两者的定义以及两者之间的关系。

从他们的定义,很容易找到归化和异化之间的差异。通过对比,这两种策略有各自的目的、优点和语言样式。归化是指翻译策略中,应使作为外国文字的目标语读者尽可能多的感“流畅的风格,最大限度地淡化对原文的陌生感的翻译策略”(Shuttleworth & Cowie,1997:59)。换句话说,归化翻译的核心思想是译者需要更接近读者。归化的目的在于向读者传递最基本精神和内容含义。这种翻译策略明显的优势就是读者可以很容易地接受它流畅的语言风格。例如,济公是个中国神话中的传奇人物。不过,外国人可能没有在这种明确的翻译方式下获得信息。因此,适合的翻译方法是找出西方国家中类似济公这样的人物。因此最终的翻译为:济公是一个中国神话中的传奇人物(类似于西方文化中的罗宾汉)。这样的翻译更容易被目的语读者所接受。“异化是指在在翻译策略中,使译文打破目地语的约束,迁就外来文化的语言特点以及文化差异。”(Venuti,2001:240)这一战略要求“译者尽可能不去打扰作者,让读者向作者靠拢。”(Venuti,1995:19)归化可能保留源语的主要信息。异化的目的是使读者产生一种非凡的阅读体验。异化可以容纳外语的表达特点,将自身向外国文化靠拢,并将特殊的民族文化考虑在内。例如,如果将“岳飞庙和墓”翻译成英语,可以翻译为:“Yue Fei’s

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2010届本科生毕业设计(论文) 毕业论文 Domestication or Foreignism-oriented Skills in Translation 学院:外国语学院 专业:姓名:指导老师:英语专业 xx 学号: 职称: xx 译审 中国·珠海 二○一○年五月

xx海学院毕业论文 诚信承诺书 本人郑重承诺:我所呈交的毕业论文Domestication or Foreignism-oriented Skills in Translation 是在指导教师的指导下,独立开展研究取得的成果,文中引用他人的观点和材料,均在文后按顺序列出其参考文献,论文使用的数据真实可靠。 承诺人签名: 日期:年月日

Domestication or Foreignism-oriented Skills in Translation ABSTRACT Translation, a bridge between different languages and cultures, plays an indispensable role in cross-culture communication. However, as a translator, we have to choose which strategy to deal with the cultural differences between the source language and the target language in the process of translation where there exists two major translation strategies--- domestication and foreignization. In this thesis, I will discuss these strategies and their application from translation, linguistics, and cross-cultural communication perspectives. In the thesis, I will first talk about the current research of the domestication and foreignization in the translation circle as well as point out the necessity for further research. Then, I will illustrate the relationship between linguistics and translation as well as between culture and translating and next systematically discuss these two translation strategies including their definitions, the controversy in history and their current studies. Besides, I will continue to deal with such neglected factors as may influence the translator’s choice of translation strategies: the type of the source text (ST), the translation purposes, the level of the intended readers, the social and historical background, the translator’s attitude and so on. Finally, from the linguistic and cultural perspectives, the thesis makes a comparative study of the application of domestication and foreignization by analyzing typical examples from the two English versions of Hong Lou Meng translated by Yang Xianyi and David Hawkes respectively. The thesis will conclude that these two translation strategies have their respective features and applicable value. I sincerely hope that this research into translation strategies will enlighten translators and make a little contribution to the prosperity of

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