Abstract
The communication of the uncertainty of a scientific finding largely determines whether that information will be translated to practice. Unfortunately, our ability to study these phenomena is restricted since existing uncertainty corpora with a diachronic perspective are limited. We analysed a historical corpus through a random sample of 167 years (1840–2007) of articles published in the British Medical Journal. Randomization was stratified according to four distinct time periods. The Uncertainty Markers (UMs) and their linguistic scope were tagged in each full-text article in order to answer the following main questions: (1) which and how many lexical and morphosyntactic UMs are used by writers in order to communicate their own uncertainty? (2) How much uncertainty (UMs + their scope) is present in each article, in each period and in the whole corpus? (3) Is there any significant variation in the use of UMs and their scope along the 167-year span? Although the analysis revealed significant differences in two of the six categories of UMs (non-verbs and modal verbs in the conditional mood), the amount of certainty and uncertainty along the four periods revealed no significant variation. The manual identification was followed by an automatic detection, whose results showed that UMs and their scope were recognised with good accuracy.
The present study has been developed within a PRIN project (Scientific Research Programme of Relevant National Interest), funded by the Italian Ministry of University and Research. The project is coordinated by Andrzej Zuczkowski (University of Macerata) and involves 4 Universities: Macerata, Bari, Rome 3 and Genoa. The study presented here shows some results reached by the University of Macerata (Andrzej Zuczkowski, Ramona Bongelli, Ilaria Riccioni), with the external collaboration of Massimiliano Valotto (University of Udine) for the informatic aspects and of Roberto Burro (University of Verona) for the statistical analyses.
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Notes
- 1.
In our corpus there were only three occurrences of the epistemic or conjectural use of will (Celle 2005). However we were unable to agree upon their epistemic interpretation. For these reason, this possible category (epistemic future) was excluded.
- 2.
The experiments were carried out using YamCha to train a classifier for recognizing the Uncertainty markers and the documents were processed using TreeTagger.
YamCha is an open source text chunker. http://chasen.org/~taku/software/yamcha/.
Treetagger is a language-independent PoS tagger http://www.cis.uni-muenchen.de/~schmid/tools/TreeTagger/
- 3.
The precision, recall and F1 are measures defined as follows:
precision = TP/(TP + FP)
recall = TP/(TP + FN)
F1 = 2 * [(precision * recall)/(precision + recall)]
True positive (TP) are uncertainty markers correctly tagged by the software, False Negative (FN) are uncertainty markers not tagged by the software and False Positive (FP) are tags incorrectly identified by the software as uncertainty markers. The precision is the accuracy of the software in identifying uncertainty markers: an accuracy of 75 % means that 3 out of 4 automatic tags are uncertainty markers. The recall measures how many uncertainty markers the software is able to automatically identify in the corpus: a recall of 75 % indicates that the software is able to automatically identify 3 uncertainty markers out of every 4 in the corpus. The F1 score is a measure that gives a weighted average of the precision and recall (Goutte and Gaussier 2005).
- 4.
In the present study we adopted a different approach, based on grammatical and syntactical rules. Partially similar approaches were previously adopted in Kilicoglu and Bergler 2010, Velldal et al. 2010. The proposed architecture and processing workflow are more cognitively plausible than the classification-based sub-symbolic approach exploited in our previous experiments (Bongelli et al. 2012). For a detailed description of the software architecture see Omero et al. (in preparation).
- 5.
We limit ourselves to only quote two of Petöfi’s works.
- 6.
These two aspects refer to what in linguistic literature is respectively called ‘evidentiality’ and ‘epistemicity’, which we are going to discuss in Sect. 2.3.
- 7.
The Atomic Text can be represented by using natural language or the canonical language of Petöfi’s Text Theory. In this paper, for the sake of simplicity, we use natural language representations.
- 8.
In particular, the syntactic structures of (1) and (2) communicate that, from the performative viewpoint, S/W states; for the aims of this paper, we prefer to use the more generic verb to communicate.
- 9.
In this descriptive proposition and in the next one, There and Then are used instead of Here and Now since the former show that the place (There) where I have seen is assumed to be different from the one (Here) where I remember and the time (Then) when I have seen is assumed to be previous to the one (Now) when communication occurs.
- 10.
Authors focusing on evidentiality provide definitions, which can be largely classified into two main types: the first considers evidentiality in terms of linguistic devices that refer to sources of information (see for example, De Haan 1999; Fitneva 2001); the second one considers evidentiality in a broader sense including modes of knowing (see for example, Chafe and Nichols 1986; Willett 1988; Cornillie 2007).
- 11.
Epistemicity has different definitions in the literature, some authors referring to the speaker’s attitude regarding the reliability of the information (Dendale and Tasmowski 2001; González 2005), others to the judgment of the likelihood of the proposition (Nuyts 2001a, b; Plungian 2001; Cornillie 2007), and yet others to the commitment to the truth of the message (Sanders and Spooren 1996; De Haan 1999; González 2005).
- 12.
In the world-constitutive proposition the epistemic adverbs, adjectives etc. are represented by the corresponding verbal expressions: the example (4) would be represented in the following way: ‘Here and Now for me it is sure that…’ or ‘Here and Now I’m sure that…’.
- 13.
The example (6) would be represented in the world-constitutive proposition in the following way: ‘Here and Now I know that…’.
- 14.
The examples (7), (8), (9) and (10) would be represented in the world-constitutive proposition respectively in the following way: ‘Here and Now for me it is probable that…’; ‘Here and Now for me it is possible that…’; ‘Here and Now I think that/pd: Pam has flown from home to Berlin yesterday’; ‘Here and Now I think that/pd: in this moment Pam is walking along the beach’.
- 15.
A total of 58 articles were written by a single author, 16 by two or more authors, and 6 are articles where the authors were not disclosed.
- 16.
1840–1880: a fascinating period for medicine in that physiology and experimentation were beginning to come up in Europe and this might be reflected in the certainty/uncertainty and hedging language; 1880–1920: the turn of the century, with all the excitement about the apparent lack of boundaries regarding what science could do and the belief that it could predict everything; 1920–1960: times of war, with the good and the bad they brought to science; 1960–2007: what we do now.
- 17.
While would and should are auxiliary verbs of the conditional mood, could and might mean also possibility, i.e., they add the meaning of possibility to the conditional mood. In this sense, as uncertainty markers, could and might have both lexical and morphosyntactic features. We treat them as morphosyntactic markers, since we decided to focus on moods rather than on lexical aspects.
- 18.
- 19.
- 20.
@inproceedings{1225791, author = {Ogren, Philip V.}, title = {Knowtator: a prot\’{e}g\’{e} plug-in for annotated corpus construction}, booktitle = {Proceedings of the 2006 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology}, year = {2006}, pages = {273–275}, location = {New York, New York}, doi = {http://dx.doi.org/10.3115/1225785.1225791}, publisher = {Association for Computational Linguistics}, address = {Morristown, NJ, USA},}
- 21.
Because statistically significant differences are more likely to occur with large sample sizes, effect sizes are necessary to understand if the differences are meaningful. In order to assess the effect sizes for our χ 2 analyses, we used Cramer’s V test. The guidelines to determine the magnitude of the effect sizes (Cohen 1988) are in Appendix.
- 22.
We included under the label “seem/s” the occurrences of: seems (50); seem (29); does not seem (6); do not seem (2).
- 23.
We included under the label “I/we think” the occurrences of: I think (44); we think (4); I’m/we are inclined to think/one is tempted to think/we are bid to think (7); I cannot help thinking (2); It is difficult to think (2); I do not think (1); I venture to think (1).
- 24.
We included under the label “appear/s” the occurrences of: appears (20); appear (17); appear to me (3); appears to me (2); do not appear (2); does not appear (2).
- 25.
We included under the label “suggest/s” the occurrences of: suggest/s (30); suggesting/to suggest (8); it is suggested (1); does not suggest (1).
- 26.
We included under the label “I/we believe” the occurrences of: I believe (19); believing (4); we believe (2); it is generally believed (1); we are justified in believing (1); we do not believe that (1); we have every reasons to believe (1); induce us to believe (1); there is reasons to believe (1).
- 27.
Hyland (1995) compared the use of hedges and boosters in eight different academic disciplines that were divided in hard (in this class, for example, he included biology) and soft sciences (in this one he included, for example, philosophy). The main result was the preference for impersonal strategies (see for example, Rundblad 2007) of hedging in hard sciences.
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Acknowledgment
Sections 1, 2, 2.1, 2.2, 2.3, 2.4 and 2.5 are mainly based on Bongelli et al. (2014) BioUncertainty. A Historical corpus evaluating uncertainty language over a 167-year span of biomedical scientific articles, in Communicating Certainty and Uncertainty in Medical, Supportive and Scientific Contexts, edited by Andrzej Zuczkowski, Ramona Bongelli, Ilaria Riccioni and Carla Canestrari, pp. 309–339, with kind permission by John Benjamins Publishing Company, Amsterdam/Philadelphia www.benjamins.com
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Appendix
Appendix
Guidelines to determine the magnitude of effect sizes (Cohen 1988)
Effect size value (Cramer’s V test) | Description | Comments |
|---|---|---|
0.00 | No Relationship | Knowing the independent variable does not help in predicting the dependent variable |
.00–.15 | Very Weak | Not generally acceptable |
.15–.20 | Weak | Minimally acceptable |
.20–.25 | Moderate | Acceptable |
.25–.30 | Moderately Strong | Desirable |
.30–.35 | Strong | Very Desirable |
.35–.60 | Very Strong | Extremely Desirable |
.60–.70 | Worrisomely Strong | Either an extremely good relationship or the two variables are measuring the same concept |
.70–.99 | Redundant | The two variables are probably measuring the same concept |
1.00 | Perfect Relationship | If we the know the independent variable, we can perfectly predict the dependent variable |
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Zuczkowski, A., Bongelli, R., Riccioni, I., Valotto, M., Burro, R. (2016). Writers’ Uncertainty in a Corpus of Scientific Biomedical Articles with a Diachronic Perspective. In: Romero-Trillo, J. (eds) Yearbook of Corpus Linguistics and Pragmatics 2016. Yearbook of Corpus Linguistics and Pragmatics. Springer, Cham. https://doi.org/10.1007/978-3-319-41733-2_10
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