Policy mobilities and methodology: a proposition for inventive methods in education policy studies

ABSTRACT

The argument of this paper is that new methodologies associated with the emerging field of ‘policy mobilities’ can be applied, and are in fact required, to examine and research the networked and relational, or ‘topological’, nature of globalised education policy, which cuts across the new spaces of policymaking and new modes of global educational governance. In this paper, we examine the methodological issues pertaining to the study of the movement of policy. Informed by contemporary methodological thinking around social network analysis and the ethnographic notion of ‘following the policy’, we discuss the limitations of these approaches to adequately address presence in policy network analysis, and the problem of representing speed and intensity of policy mobility, even while these attempt to solve the problem of relationality and territoriality. We conclude that the methodologies of policy mobility are inexorably intertwined with the (constantly) changing phenomena under examination, and hence require what Lury and Wakeford describe as ‘inventive methods’.     

Anticipating education: governing habits,memories and policy-futures

ABSTRACT

The use of data to govern education is increasingly supported by the use of knowledge-based technologies, including algorithms, artificial intelligence (AI), and tracking technologies [Fenwick, T., E. Mangez, and J. Ozga. 2014. Governing Knowledge: Comparison, Knowledge-Based Technologies and Expertise in the Regulation of Education. New York, NY: Routledge]. New forms of datafication and automation enable governments and other powerful stakeholders to draw from the past to construct images of educational futures in order to steer the present. This paper examines the competing conceptions of time and temporality that AI posits for policy and practice when used to anticipate educational futures. We argue that most educational futures are already delineated, and machinic expressions of time are the chronologies, habits, and memories that the educated subject inhabits rather than produces. If resetting educational habits and memories can be an alternative to algorithmic anticipations of education then we believe, paradoxically, that machines may help to reset them by accelerating them.     

Experiments with dictionary-based CLIR using graded relevance assessments: Improving effectiveness by pseudo-relevance feedback

Research on cross-language information retrieval (CLIR) has typically been restricted to settings using binary relevance assessments. In this paper, we present evaluation results for dictionary-based CLIR using graded relevance assessments in a best match retrieval environment. A text database containing newspaper articles and a related set of 35 search topics were used in the tests. First, monolingual baseline queries were automatically formed from the topics. Secondly, source language topics (in English, German, and Swedish) were automatically translated into the target language (Finnish), using structured target queries. The effectiveness of the translated queries was compared to that of the monolingual queries. Thirdly, pseudo-relevance feedback was used to expand the original target queries. CLIR performance was evaluated using three relevance thresholds: stringent, regular, and liberal. When regular or liberal threshold was used, a reasonable performance was achieved. Using stringent threshold, equally high performance could not be achieved. On all the relevance thresholds the performance of the translated queries was successfully raised by pseudo-relevance feedback based query expansion. However, the performance of the stringent threshold in relation to the other thresholds could not be raised by this method.     

Transitive dictionary translation challenges direct dictionary translation in CLIR

The paper reports on experiments carried out in transitive translation, a branch of cross-language information retrieval (CLIR). By transitive translation we mean translation of search queries into the language of the document collection through an intermediate (or pivot) language. In our experiments, queries constructed from CLEF 2000 and 2001 Swedish, Finnish and German topics were translated into English through Finnish and Swedish by an automated translation process using morphological analyzers, stopword lists, electronic dictionaries, n-gramming of untranslatable words, and structured and unstructured queries. The results of the transitive runs were compared to the results of the bilingual runs, i.e. runs translating the same queries directly into English. The transitive runs using structured target queries performed well. The differences ranged from −6.6% to +2.9% units (or −25.5% to +7.8%) between the approaches. Thus transitive translation challenges direct translation and considerably simplifies global CLIR efforts.     

Psycho-politicising educational subjectivity: A posthumanist consideration of Rancière and Lacan

Drawing on the aesthetic theory of Jacques Rancière and the Lacanian conception of lack, this paper offers an intervention into the notion of subjectivity which can be applied in critical studies of education. Critiquing the progressive and knowledge-oriented ideology of neoliberal systems, Rancière depicts a world in which politics turns out to delimit the subject’s perceptual experience and in this way, argues that what remains out of this ideological demarcation is susceptible to a challenge of the social order on which an ideology is based. While Rancière presents a meticulous reading of current pedagogic institutions, Lacan provides us with a definition of subject having the capacity to challenge the delimiting social order. The latter is achieved by theorising a subject inflicted by a double lack, realised both at the subjective and objective levels. This double negativity gives rise to the emergence of desire in the subject which in Lacan is the source of emancipation as it makes the subject not be satisfied by a given achievement, hence replacing one desire after another.     

Dictionary-Based Cross-Language Information Retrieval: Problems, Methods, and Research Findings

This paper reviews literature on dictionary-based cross-language information retrieval (CLIR) and presents CLIR research done at the University of Tampere (UTA). The main problems associated with dictionary-based CLIR, as well as appropriate methods to deal with the problems are discussed. We will present the structured query model by Pirkola and report findings for four different language pairs concerning the effectiveness of query structuring. The architecture of our automatic query translation and construction system is presented.     

Evaluating the effectiveness of relevance feedback based on a user simulation model: effects of a user scenario on cumulated gain value

We propose a method for performing evaluation of relevance feedback based on simulating real users. The user simulation applies a model defining the user’s relevance threshold to accept individual documents as feedback in a graded relevance environment; user’s patience to browse the initial list of retrieved documents; and his/her effort in providing the feedback. We evaluate the result by using cumulated gain-based evaluation together with freezing all documents seen by the user in order to simulate the point of view of a user who is browsing the documents during the retrieval process. We demonstrate the method by performing a simulation in the laboratory setting and present the “branching” curve sets characteristic for the presented evaluation method. Both the average and topic-by-topic results indicate that if the freezing approach is adopted, giving feedback of mixed quality makes sense for various usage scenarios even though the modeled users prefer finding especially the most relevant documents.     

s-grams: Defining generalized n-grams for information retrieval

n-grams have been used widely and successfully for approximate string matching in many areas. s-grams have been introduced recently as an n-gram based matching technique, where di-grams are formed of both adjacent and non-adjacent characters. s-grams have proved successful in approximate string matching across language boundaries in Information Retrieval (IR). s-grams however lack precise definitions. Also their similarity comparison lacks precise definition. In this paper, we give precise definitions for both. Our definitions are developed in a bottom-up manner, only assuming character strings and elementary mathematical concepts. Extending established practices, we provide novel definitions of s-gram profiles and the L₁ distance metric for them. This is a stronger string proximity measure than the popular Jaccard similarity measure because Jaccard is insensitive to the counts of each n-gram in the strings to be compared. However, due to the popularity of Jaccard in IR experiments, we define the reduction of s-gram profiles to binary profiles in order to precisely define the (extended) Jaccard similarity function for s-grams. We also show that n-gram similarity/distance computations are special cases of our generalized definitions.